{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_table_md = \"\"\"\n",
    "| 动作 | 优势帧 | 版中距离 | 版边距离 | 特殊情况 |\n",
    "| --- | --- | --- | --- | --- |\n",
    "| SA3 | +14 | 12 | 12 | 固定位置版边，绿冲无法及时防御 |\n",
    "| SA1 | +14 | 38 | 0 | 有利帧取决于击中时的浮空高度 |\n",
    "| SA2 | +17 | 15 | 15 | 与SA3相似 |\n",
    "| 盾投 | +18 | 15 | 13 | |\n",
    "| 盾踢 | +22 | 15 | 0 | |\n",
    "| 前投 | +23 | 26 | 13 | |\n",
    "| 斗反 | +23 | 35 | 0 | |\n",
    "| 2HK | +29 | 0 | 0 | |\n",
    "| 轻双剑 | +31 | 12 | 0 | |\n",
    "| 盾打 | +31 | 19 | 0 | |\n",
    "| 5HP~HP | +35 | 30 | 0 | |\n",
    "| [SA1] | +35 | 29 | 17 | |\n",
    "| 迸放 | +35 | 37 | 0 | |\n",
    "| 短剑 | +36 | 27 | 0 | |\n",
    "| 中双剑 | +36 | 16 | 0 | |\n",
    "| 正蹬 | +36 | 22 | 0 | |\n",
    "| [短剑] | +40 | 25 | 21 | |\n",
    "| 超人拳 | +42 | 29 | 0 | 轻、中代入连段为+43到+44 |\n",
    "\"\"\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def read_md_table(md_fmt_table):\n",
    "    lines = md_fmt_table.strip().split('\\n')\n",
    "    header = [x.strip() for x in lines[0].split('|') if x.strip()]\n",
    "    data = []\n",
    "    for line in lines[2:]:\n",
    "        data.append([x.strip() for x in line.split('|') if x.strip()])\n",
    "    return pd.DataFrame(data, columns=header)\n",
    "\n",
    "df = read_md_table(data_table_md)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>move</th>\n",
       "      <th>adv</th>\n",
       "      <th>dist</th>\n",
       "      <th>dist_edge</th>\n",
       "      <th>特殊情况</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>SA3</td>\n",
       "      <td>14</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>固定位置版边，绿冲无法及时防御</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>SA1</td>\n",
       "      <td>14</td>\n",
       "      <td>38</td>\n",
       "      <td>0</td>\n",
       "      <td>有利帧取决于击中时的浮空高度</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>SA2</td>\n",
       "      <td>17</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>与SA3相似</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>盾投</td>\n",
       "      <td>18</td>\n",
       "      <td>15</td>\n",
       "      <td>13</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>盾踢</td>\n",
       "      <td>22</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>前投</td>\n",
       "      <td>23</td>\n",
       "      <td>26</td>\n",
       "      <td>13</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>斗反</td>\n",
       "      <td>23</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2HK</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>轻双剑</td>\n",
       "      <td>31</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>盾打</td>\n",
       "      <td>31</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>5HP~HP</td>\n",
       "      <td>35</td>\n",
       "      <td>30</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>[SA1]</td>\n",
       "      <td>35</td>\n",
       "      <td>29</td>\n",
       "      <td>17</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>迸放</td>\n",
       "      <td>35</td>\n",
       "      <td>37</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>短剑</td>\n",
       "      <td>36</td>\n",
       "      <td>27</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>中双剑</td>\n",
       "      <td>36</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>正蹬</td>\n",
       "      <td>36</td>\n",
       "      <td>22</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>[短剑]</td>\n",
       "      <td>40</td>\n",
       "      <td>25</td>\n",
       "      <td>21</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>超人拳</td>\n",
       "      <td>42</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>轻、中代入连段为+43到+44</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      move  adv  dist  dist_edge             特殊情况\n",
       "0      SA3   14    12         12  固定位置版边，绿冲无法及时防御\n",
       "1      SA1   14    38          0   有利帧取决于击中时的浮空高度\n",
       "2      SA2   17    15         15           与SA3相似\n",
       "3       盾投   18    15         13             None\n",
       "4       盾踢   22    15          0             None\n",
       "5       前投   23    26         13             None\n",
       "6       斗反   23    35          0             None\n",
       "7      2HK   29     0          0             None\n",
       "8      轻双剑   31    12          0             None\n",
       "9       盾打   31    19          0             None\n",
       "10  5HP~HP   35    30          0             None\n",
       "11   [SA1]   35    29         17             None\n",
       "12      迸放   35    37          0             None\n",
       "13      短剑   36    27          0             None\n",
       "14     中双剑   36    16          0             None\n",
       "15      正蹬   36    22          0             None\n",
       "16    [短剑]   40    25         21             None\n",
       "17     超人拳   42    29          0  轻、中代入连段为+43到+44"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.rename(\n",
    "    columns={\n",
    "        \"动作\": \"move\",\n",
    "        \"优势帧\": \"adv\",\n",
    "        \"版中距离\": \"dist\",\n",
    "        \"版边距离\": \"dist_edge\",\n",
    "    },\n",
    "    inplace=True,\n",
    ")\n",
    "\n",
    "### wash data\n",
    "\n",
    "# 1. remove trailing \"`\" in move column\n",
    "df[\"move\"] = df[\"move\"].str.replace(\"`\", \"\")\n",
    "\n",
    "# 2. remove \"+\" in adv column and convert to int (if fail to convert, remove that row)\n",
    "df[\"adv\"] = df[\"adv\"].str.replace(\"+\", \"\")\n",
    "df = df[df[\"adv\"].str.isnumeric()]\n",
    "df[\"adv\"] = df[\"adv\"].astype(int)\n",
    "\n",
    "# 3. remove rows with \"*\"(missing data) in dist or dist_edge columns\n",
    "df = df[~df[\"dist\"].str.contains(\"\\*\")]\n",
    "\n",
    "# 4. factorize dist and dist_edge columns\n",
    "# order = [\"贴脸\", \"中距离\", \"较远\", \"非常远\"]\n",
    "# df[\"dist\"] = pd.Categorical(df[\"dist\"], order)\n",
    "# df[\"dist_edge\"] = pd.Categorical(df[\"dist_edge\"], order)\n",
    "df[\"dist\"] = df[\"dist\"].astype(int)\n",
    "df[\"dist_edge\"] = df[\"dist_edge\"].astype(int)\n",
    "\n",
    "df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "def scatterplot_with_text(data, x, y, text, fontsize=8, **kwargs):\n",
    "    ax = sns.scatterplot(x=x, y=y, data=data, **kwargs)\n",
    "    texts = []\n",
    "    for i in range(len(data)):\n",
    "        texts.append(ax.text(data[x][i], data[y][i], data[text][i], fontsize=fontsize, ha='center', va='bottom'))\n",
    "    return ax"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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9dOhQtr4LHjhwgLi4ODw8PLj77rtzFHN6Tp06BaStD++6GPDfxPxDDz3EzJkzWbhwIa+88kqqO8S1ZpqISM4pMS8C9O7dm4cffhgfH580+zp06MCECRMYO3YsTqeTYcOG8eyzzxqLukLKwn4zZ840bt+z2+3GavXplbFxuXYm/fLly5WYFxEppPbt20eJEiUoW7assa1Nmzbs2bOHhx9+GJvNxscff5xr491ojXkRERHJO66Z8rNmzaJGjRrptgkLC8PpdBIQEMCOHTvSbXPw4EFCQ0MznXl/rdmzZwPQtGlTvLy8Uu279vtpdu3btw9IuVP8Wq6F5P/7/bhjx47ccccdHDp0iC1btvDtt98CKTPpRUQk55SYF/n/0kvKu4wePZoSJUowYMAASpcuTWRkJO7u7lSoUIE2bdrw3HPPERQUZLTftGkTUVFRQMZlbAAqVqxI5cqVOXHiBN9//z2jR4/OvRMSEZFccezYMdq2bYvD4WDKlCn07NnT2FexYkW2bt1KZGQkgYGBuTZmcnJyrvUlIiIieaNGjRo0atQo3X2u0qZmsznDNjkRHh5ulKgZOnRomv2uzw7Z/Qxx6tQpjh8/jslkok6dOqn2uWrP+/n5pdpuNpsJDQ1lwoQJhIaGcuzYMdzd3Y0FakVEJGeUmBfJJtds+O+//z7LD1b3339/tmcsuBbLyUzLli2vawaEiIjcuL179xIfH09sbCy9evVi2bJlTJ06leLFiwPg5eVFuXLlcnVMV13ae+6554b62b9/P7Vr186NkERERKSAOBwO+vfvT2xsLFWqVOGRRx5J08aVkM9uKbwff/wRSLm4EBAQkGqfawb/fxPzAIMGDeK9997j2LFjAHTt2jXVHYUiIpJ9KgImIiIikonu3buzb98+mjZtCsB3331HzZo1WbFiRZ6MFx8fb3y59vT0xGw2G/ssFkuWD5datWopKS8iInKTS0pKol+/fkYi/bPPPku35F1SUlKqP7PiWhenQ4cOafZduXIFgCJFiqTZd+edd9KiRQvjdXqz90VEJHuUmBcRERHJQtWqVfn1118ZP3487u7uhIeH07lzZwYNGpTrY129etV4vmfPHv78808A3Nzc+Ouvv7DZbBk+Tpw4YXxZ79evX67HJiIiInnHlRA/ffo0f//9N3a7nQ4dOrBgwQIA+vbtywMPPJDusa677bKTmD9y5AhbtmzBZDKl+3nhzJkzAMbdgdeaPXs2v/76q/F66tSpWrBeROQ6KTEvIiIikg3u7u68/PLLbNiwwShd06BBg1wfJyIiwnhesmRJgoKCuOeee0hOTmb69OmZHjtz5kwcDgd+fn4MGDAg12MTERGRvDFr1ixeeuklAP755x9q1KjBiBEj6NOnD/fddx/BwcF89tlnGR6fkJAAgM1my3KssWPHAimLtlavXj3VvsuXL/P7778DpCpRk5iYyEsvvURoaCgOh4PBgwdTpEgRvv32W9q3b09YWFjOTlhERFRjXkRERCQnmjdvzr59+1izZg29e/e+7n5iY2Px8PBIVX4GUr6MA3h4eBgLyj7xxBNs376dGTNm8PLLL+Pt7Z2mP5vNxrRp0wAYOHBgmnqxIiIiUjh9+OGHLFq0CG9vb5YsWYLFYuH111/n448/BqBMmTJUqFCBiRMnUq1aNQICAvD398fHxweTyQRAu3btqFOnDj4+PmzcuBGbzUZ8fDwxMTFERUVx//33ExwczNy5c1m2bBkAw4cPB1Jm248YMYKYmBg2b96MzWajXLly+Pv7A7B8+XLGjBnD4cOH8fDw4KOPPuKZZ56hR48edOjQgfXr11OjRg1Gjx7NkCFD8PHxKYCfoojIzUeJebltHDx4sECPFxGRW0dgYGCmSXnX7eQAK1euJCYmhvPnz3PmzBlOnTrFiRMnOH/+PGvXrqVt27apjj158iQA5cuXN8rS9O7dm1dffZXw8HA+/vhjxowZk2bMzz77jPPnz2OxWHj++edv/CRFREQkT7nKzixatAiAjz76iIceegiAtm3b8v333/Puu++yc+dOzp8/z2+//XZd4wQFBTFw4EC2bNnC4MGDAejRowetW7cGwGw2ExYWxjfffGMcM3r0aGbOnMmHH35ofBeuUKECX3/9Nffeey8ALVu2ZMOGDXTu3JkLFy4wcuRI3nzzTcaMGWPMyhcRkYwpMS+3PNdK8qGhobnan4iI3D6SkpK4ePEiFy9eJCIiggsXLqR5hIeHG3/GxMQYxz7xxBPp9mkymVKVrXE5evQoAJUrVza2eXl5MWLECIYPH87777/PgAEDKFGihLE/IiKCCRMmAPDcc89Rvnz5XDlvERERyTseHikpmcaNG+Pu7s7AgQNT7e/atStdu3blwoUL/PTTT+zbt4+///6bM2fOEBERwZUrV4iJiUlT491sNuPt7Y2vry8BAQE8++yzWCwWgoOD6dy5M5s2bWLKlCmpjunVqxdxcXHUqVOHLl26cPfdd7Nv3z5OnTqFm5sbgwYNYuLEiWm+Dzdu3JgDBw7wwgsv8PXXXxMbG5thHXwREUlNiXm55QUHB3Po0CGio6NvuC8/Pz+Cg4NzISoRESnMVq1axeuvv87ly5e5dOkSUVFROJ3ObB1brFgxKlSowOnTpwHo1q0blSpVokyZMpQtW9Z4lC5dGk9PzzTHb9y4EYBatWql2v7000/z6aefcurUKZ555hm+/fZbY9+zzz5LZGQkJUuW5OWXX77OsxYREZGC8PHHH1OxYsUM95csWZJevXrRq1evdPc7HA4cDgcmkwkPDw+jvM1/FS9enG+++YZTp04Z5fJcOnXqRKdOnVJtq1u3LtOnTyckJIR69eplGt+CBQsYNWoUP/30U56swSMicitSYl5ueSaTiZCQkIIOQ0REbiLR0dHs2bMn1baAgADKli1rJNhLly5NmTJlKFOmjPG8dOnSWCwWfvrpJ9q1awfA1KlTKV68eLbGvXDhgnG7+H+/1Hp7ezN9+nTat2/P4sWLmTlzJk8++STz5s0zboGfMGGCUQ9WREREbg4mk4lSpUpd9/Hu7u5G+bvsyOwiwH/17Nkz221r165N7dq1s91eROR2p8S8iIiIyH80btyYBQsWGLPby5Qpk+6CqxnJ7uz6/1q3bp3x3FX39VoPPPAAAwYMYMaMGTz11FNcvnyZV199FYDHHnss18q2iYiIiIiISN5SYl5ERETkPypVqkSlSpWu+/jrTczPmDEDgPr161OmTJl020yZMoU//viDnTt3MmLECCBlUTfXsSIiIiIiIlL4uRV0ACIiIiK3mv8uwpYdhw4dYtOmTQD06dMnw3YWiyVNjdkHHngAHx+fHI8pIiIiIiIiBUOJeREREZFclpycbDzP7uz5yZMnA+Dj40P//v3TbXPo0CG6dOnCc889B6TUvQf49NNPqVWrFvPmzSMxMfEGIhcREREREZH8oFI2IiIicttzOp0cOXKE6OjoG+7Lz88vVXI8ISEhy2N27NjBV199BcDgwYMpUqSIsS8xMZE1a9YwY8YMVq1ahdPpxNPTk1deeYWRI0cyZcoUXn75ZQ4dOkTfvn15/vnnefTRR+nWrRstWrTAbDbf8DmJiIiIiIhI7lJiXkRERG57R44coXr16rnW36RJk4znNpst07YOh4OnnnqK5ORk/Pz8GD16NOHh4WzcuJF169axbNkyLl++DIC7uzs9e/bk9ddfp0qVKgC89NJLdOjQgddee42lS5dy6dIlpk+fzvTp0/Hz86N58+Y8+uijGc7CFxERketz8ODBDPfZ7Xbjz507d+b4eBERufUpMS8iIiK3PddM+VmzZlGjRo3r7ufgwYOEhoZy9epVY1tWiXl3d3dee+01XnrpJZ5++ml8fX1p2rQp+/btM9oUK1aMPn36MGTIEIKCgtL0ERISwuLFizl8+DBTpkzhm2++ITIykujoaH777TemT59+3eckIiJyK7t8+TLdu3dn7969dOnShYkTJxIYGJiqzZQpUxgyZAhubinVgP38/AAIDQ3NsN+5c+fi7+9PVFQUXbp0yTQGV38iInJ7UWJeRERE5P+rUaMGjRo1uuF+OnTowLhx47Ld/uGHH6Z169Z4e3tjNptZsGABLVq0oH379nTp0oWHHnoIq9WaZT8hISF89tlnfPTRR6xbt44VK1YQFBREuXLlbuBsREREbl1Dhgzhp59+AlIu0P/666+sW7eOSpUqAXD27FmGDx+Oj48PTzzxBADBwcEcOnQo0xJ4YWFhOJ1OAgIC2LFjR4bt/Pz8CA4OzsUzEhGRm4US8yIiIiKFgGshV4Dq1atz4cIFTCbTdfVlNpvp2LEjHTt2zK3wREREbjm//fYbixYt4vPPP6d379588803vPDCCzRt2pTZs2dz991307NnTzw9PenUqZNxnMlkIiQkJNO+16xZQ2JiImazOVcu+ouIyK1HiXkRERGRQuh6k/IiIiKSPZ9++in33nsvTz/9NAADBgygdu3atG/fnvbt2xvtZsyYQfHixQsqTBERuUUpMS8iIiIiIiIit523336bv/76K9W2Ro0asWXLFvr27cv58+cZOXIkTz75ZAFFKCIitzK3gg5ARERE5Gbx+++/M2jQICIiIgo6FBERkULNbrfj5eWFyWTK8OHr62u0HzdunLE9o4XT+/fvj8lk4s477zS2nTx5Mt2+3dzcKFq0KPfeey8ffvgh8fHxafq78847adeuXZrt1atXZ/fu3Zw/f57nn38+3eNMJhM9evTI8Pw7dOhA165dmT9/frrneO3D09OTsmXL0q1bN3755ZcM+xQRkVuLEvMiIiIi2bB161ZatmzJl19+yenTpws6HBERkULt999/x2azYTKZsFgs6T6ys7B5Tnh4eBh9m0wmrly5wrZt23jxxRdp3LgxFy5cyNXxboQrTk9PT+x2O+fPn2fJkiW0adOGUaNGFXR4IiKSD5SYFxEREcmG119/nZiYGL766isaNGhQ0OGIiIgUatu3bwegc+fO2Gy2dB8XL17M1TGnTp1q9J2UlMTJkyeZOHEiVquVAwcO0KdPn1wd70bExMRgs9lISEjAZrPx22+/8fDDDwMwceJEFi5cWMARiohIXlNiXkRERCQbPvvsM3bu3En//v0LOhQREZFCz5WYb9SoUYGMbzKZqFixIiNGjGDy5MkArFu3jj/++KNA4smMxWKhcePGLFmyhMaNGwPw/vvvF3BUIiKS15SYFxEREcmGu+66SzPlRUREsmnr1q0ANG3atIAjwZiJDv8XV2FkMpno2rUrAPv27SMuLq5gAxIRkTylxLyIiIiIiIiI5JqzZ89y9uxZrFYrTZo0KehwKF68uPH88uXLBRhJ1lyxOp1Orly5UrDBiIhInlJiXkRERERERERyzbZt2wC44447ePrpp6latSpeXl4EBgbSokULPv/8c+x2e77FExERYTwvVqxYvo17PVyxmkwmihYtWsDRiIhIXlJiXkRERERERERyzZYtWwA4deoUc+bMwcvLi+bNm1O8eHF+/fVXnnnmGerXr5/h4q9FihTBarWmecybN++64lmyZInxvFmzZtfVR3oWL16cbpxWq/W6+ktOTmbZsmUANGjQAC8vr1yLVURECh8l5kVEREREREQk12zevBlISYIfOnSIAwcOsG7dOo4ePcq6desoWrQof/75JwMGDEj3+ISEhHQfycnJ2Y4hMTGRY8eO8c477zB8+HAAOnbsSM2aNW/8BP+/5OTkDGPNiejoaDZv3kzXrl3ZtWsXAKNGjcq1OEVEpHDyKOgAREREREREROTWMXXqVM6ePUuHDh3w9vZOta9t27bMmTOHzp07s3z5co4ePcpdd92Vqk18fHy6s8779+/PnDlzMhx34MCBDBw4MN19DRo0yPTY69G9e3cWLVqU7j6TyZTpsWazOcN9r732Gt26dbuh2EREpPBTYl5ERETk/zt48GCBHi8iInIryGrB106dOlGmTBnOnz/P6tWr0yTmr5eHhwfu7u4AuLm54e/vT/Xq1Xn00UcJDQ3FYrHkyji54dpYzGYzJUuW5J577uHpp5/m3nvvLcDIREQkvygxLyIiIrc9Pz8/AEJDQ3O1PxEREUlfhQoVOH/+PMePH8+1PqdOnZpheZzCJiYmBg8PpWRERG5n+l9AREREbnvBwcEcOnSI6OjoG+7Lz8+P4ODgXIhKRETk5mWz2TJdBPXChQv5GI2IiEjho8S8iIiI3PZMJhMhISEFHYaIiMhNb9myZTz//PM0bdqUhQsXptvm5MmTnDhxAkAXs0VE5LalxLyIiIiIiIiI5Ipy5cpx+vRpIiIiOHXqFBUrVkzT5vXXXwdSaqt36dIlv0MUEREpFNwKOgARERERERERuTU0bNiQVq1aER8fT7du3Thz5oyxLzY2lmHDhjF37lwAnnvuOSpUqFBQoYqIiBQozZgXERERERERkVwzZ84cWrduze7du6lUqRIhISFYLBaOHj1KTEwMJpOJ5557jvfee6+gQxURESkwSsyLiIiIiIiISK4pX748v//+O5MmTWLRokUcPXoUq9XKnXfeScuWLXnqqaeoUaNGQYcpIiJSoExOp9NZ0EFI4VK8eHEiIyMJDAzk4sWLBR2OpGPNmjUkJibi6enJgw8+WNDhiNyy9F4TyT96v4nkD73XRPKH3msi+UfvN7lZqca8iIiIiIiIiIiIiEg+UmJeRERERERERERERCQfKTEvIiIiIiIiIiIichPr2rUrd999N+vXry+wGN58803GjBnDlClT8mW8X3/9ld69e/PKK69w4sSJNPsjIiLyJY7rpcVfRURERERERERERG5iR48e5ciRIyQmJqbZt337dsLDw/Hy8sLd3T3Lvlq2bImHR87Txj/++CPbt2+nZs2aDB06NMfHp2fPnj2MHTuWSZMmUbNmzVT7Tp8+zYIFC/D09GTs2LGp9p09e5a6detSs2ZN3n33XZo0aZIr8eQmJeZFREREREREREREbmJWqzXVn9eaPn06c+bMyVY/JpMp3eR+dvj6+gJQsWLF6zr+v2w2G3379uXQoUM0aNCA1157jVGjRhkXDWJiYgCoX78+3t7exnGxsbF07dqVyMhIrl69SoUKFXIlntymxLyIiIiIiIiIiIjITSIpKQmbzYa3tzdubimVyi0WCwAeHh44nU4SEhJISEggICCANm3aULRoUaxWKydPnmTRokX4+voyatQoo8/jx48zZ84cihYtel2z5QEjOe7n53eDZ5jCarWyY8cORowYwbRp03j11VcpUaIEgwYNAuDixYsA1K1b1zgmKSmJ7t27s2fPHho3bszatWsJCAjIlXhymxLzIiIiIiIiIiKZOHPmDOXKlcNkMhV0KCIi7N69m3vuuQcAd3d33N3dsdvtALRp04akpCSjbXx8PH369KFPnz4ATJo0iUWLFlG7dm1eeeUVo92yZcuYM2cOxYsXv+64HA4HAGaz+br7+C9fX1+mTp1KixYtCAsLM5LykFK+B6B27drGtn///ReHw0H9+vULdVIelJgXEREREREREcnQvn37qFevHqNHj2bChAkFHY6ICCaTCU9PT7y9vfH09MTd3Z3IyEgSExMJCAggOTnZmDH/X1u3bgWgadOmqbZHR0cDUKRIkeuOy5WYv95SONeKjY0lPj4eT09PLBYL3bt3T3Nx9K+//gJSJ+bLly/PmjVrsNvtmM3mVD+LhIQESpYsWWgusroVdAAiIiIiIiIiIoVVlSpVqFChAu+99x6//PJLQYcjIkLjxo1JSEjg8uXLhIeHc/78eRo2bAjA999/z6VLl4iNjSUpKSlVzfkzZ86wYsUKADp06JCqT1e99huZYR4XFwekJNVv1JdffkmJEiUICAjAarXi5uaGyWRK9di5cycAzZo1S7PP09MTk8mEu7s73t7eFC1alFKlSuVKbLlFM+ZFREREREREJMdmz57NE088ke6+fv36MXv27PwN6Ab1798/w8URx4wZw3vvvUffvn35448/KFasWD5HJyJy40aPHk1SUhKVK1emZcuWqfa5ZszfSGL+zJkzAERGRl53Hy6NGjXitddeM2bMWyyWVDPdFy5cyLZt22jUqJFRpic9ycnJ2Gw2Y8a8p6fnDceWW5SYFxEREREREZHr5u7unmahwNysL5xfzGazsXiiS1JSEg6Hg6CgIEaPHs0777zDU089xTfffFNoSiGIiGTHlClT+PrrrwEYN25cqt9hdrudn376CYASJUpc9xjnzp0DIDw8/Lr7SE5O5tKlS9SqVYv69esbNfRdi9wC/P3334wcORKLxcKcOXMIDg7Oss/ExEQSExOJiorCarXm2gK1N0KlbERERERERETkur3yyivYbLZUjy+//LKgw8qxL7/8Ms15XLsw4rhx47j77rtZvHgxc+fOLcBIReR2d9ddd1GiRAnKly/PnXfeSZUqVdizZw8A3bt3p3z58pQsWZIiRYrQtWtXhg0bxrBhwwDo1q2bMcP8nXfeoVGjRpQpU4aff/4ZSCkLcz3++ecfo6b9P//8w+XLl6+rn/Pnz1OiRAn8/f3x8vIyauhfW6amatWqxMfHk5CQQEhISJoyNv99uLu74+XlRUBAACVLlmTSpEnXFVtu04x5EREREREREclTycnJzJkzh6+++or9+/eTkJBAqVKlaNWqFaNGjcpytiNAy5Yt2bRpE02aNGH79u05Gn/48OFMmjSJDRs2pCnfkF1ms5kFCxZQr149hg4dSvPmzalcufJ19SUiciMSExNJSEjA6XTi4eGBu7s7fn5+2Gw2IiIiCAwMxOl0YrfbOXjwIBs3bgSgXr16qS6c3nPPPbz88ssAeHl5MWjQIB5//PHrimnz5s3Gc6fTydKlS3nyySdz3I+/vz+vvvoqVqsVs9lszJg3mUzY7XYmTpzIhQsXqFevHqGhoWmOnzx5Mv/88w/9+vWjQYMGOJ1OHA4HycnJ2O12EhISrvviQ25TYl5ERERERERE8kxsbCxdunQxZmMCmEwmTp06xezZs1m8eDE//vhjpomSyMhItmzZAsCOHTsICwujVKlS2Rr//fffz7XZkUFBQXz00UcMGjSI3r178+uvv6Yp4yMiktf++eefNNt2795Nw4YNqV27Nrt370617/jx47z77rt8+OGHqUq4NGvWjFdeeYW7776b1q1b31B5F1di3tPTk8TERGbMmHHdifk333wzzfYLFy7w6KOPcuHCBWrWrMmPP/5IyZIl07SrU6cOLVu2ZP369YwePTpbF34LikrZiIiIiIiIiEieGTZsGD///DNeXl7MnDmTK1euEBMTww8//ECpUqWIjY2ld+/eJCYmZtjHqlWrcDgcQMpMzBUrVmQ5rtPp5J133mHUqFG5di4AAwYMoEuXLmzfvp233347V/sWEckLVatWpW/fvjzxxBN069bNeDz++OMcPnyYefPmGfteeOGFHPfvdDqNGvUvvvgiAQEB/Pbbb8ZM/Ru1bNkyatasya+//krz5s359ddfUyXlw8LC2LhxI1OmTGHmzJl4e3tz7tw5GjVqxJQpU7Db7bkSR27TZV0RERERERERyROXL19m3rx5ALz88supyg506tSJOXPm8MADD3Dq1CmWL1/Oo48+mm4/33//farXy5cvZ+DAgRmOe+nSJfr06cPq1aupUKECp0+fvvGT+f9MJhMzZsxgx44dvPXWWzzwwAM0adIk1/oXEcmOTz/9lMuXL1O3bl06d+6cZfvw8HCWLFmSZbs6derkOJZt27Zx6tQpAB5//HGioqKYOnUqb7zxxnWXDwM4dOgQL7/8svF/QNmyZWncuDEjRozg33//5dSpU5w6dYqYmJg0x/r4+BAdHc2wYcN477336NOnD+3bt+fuu+/G29v7umPKTUrMi4iIiIiIiEie+Ouvv0hKSgKgbt26afa3bdsWX19f7HY7+/fvTzcxb7PZWLduHQBvvfUWr776Kj///DOxsbH4+PikO+5TTz3F6tWradGiBYsXL0633MH1cjqdREREMGbMGJ577jm6devGvHnzUsXimp1pt9vZuXNnhn35+fkRHByMyWTKtfhE5Pbwyy+/8P3331O/fv00ifnk5GQSExOJi4vDy8vLeACEhITw4osvpunv8OHDTJ48GU9PzxzH8vHHHwNw9913U7t2bYYOHcq0adPYuHEjy5cvp0uXLtnuKykpifXr1zN37ly++eYbkpOTKVKkCF988QWHDx/m9ddfB8BqtVK1alVKlixJTEwM9957L88++yxVqlShUqVKFCtWjF27djF27FjWr1/PhAkTmDBhAm5ubgQHB/Pzzz9nuyRaXlFiXkRERERERETyhK+vr/F88+bNdOzYMdV+k8lEdHR0pn2sX7+e2NhYAgICGD58OB999BGRkZGsXbuWRx55JN1jrFYrn3zyCc888wxubrlbxffIkSNUr17deH3u3Dlat26dqs3cuXPx9/cnKioqy4TUoUOHCAkJydUYReTWFxcXB0DTpk1Tbd+zZw/u7u7G63nz5tG7d29jW5kyZRgwYECa/tavX39difmDBw8aM/GHDRsGQPXq1XnkkUdYsmQJw4cPp3379lgslmz19/nnnzN8+HDjAmeXLl34/PPPKVOmDGfPnqVVq1ZUrlyZMmXKYDKZGD16NO+99x41a9bkscceS9VXw4YN+emnn9i7dy9Tpkzhu+++Izo6mueee67Ak/KgxLyIiIiIiIiI5JHq1atTq1YtDhw4wKRJkwgICOD55583Zm5mh6uEQbt27bBarTz44IPMnz+f5cuXZ5iYnzFjxnXN+swO14WEWbNmUbVqVZ544gn+/vtv3nnnHdq0aQOk1Dt2Op0EBASwY8eOdPs5ePAgoaGhWV6YEBFJT0REBECaC3sWi4XSpUtjt9uJjY01Fqi+NlmfmZz+7nzmmWdITk4mJCSEnj17GtvfeOMNli9fzvHjxxk5cqQxqz4rzz77LBUqVODdd9/lzTffxMfHhyeeeAKLxYLFYsHT0zPVXUb79u0DUu4g6N27t7HddddAbGwsb7/9NrNmzeLzzz9nx44dmS42np+UmBcRERERERGRPGEymVi0aBFt27bl/PnzjB07lsmTJ/PEE08waNAgqlatmunxycnJxkKvrtn2HTt2ZP78+caCsOklm/IqKX+tGjVq0KhRI5YuXUrDhg2ZNGkSI0eOxN3dnTVr1pCYmIjZbKZRo0Z5HouI3H7++ecfACpUqJBqe82aNdm9e3ea9tm9eygnpbU++eQTNm3aBMAHH3xgXASAlN+Rw4YN48MPP+TTTz/lgQceoEOHDtnqt2vXrnTt2hVIWVNkw4YNRmLeYrGkivHq1asAnD9/PtVisw6HA7vdTkxMDJcvXwZS7qZq0aJFts8vr+Xu/VwiIiIiIiIiIteoXr06+/fvZ9CgQXh6enLx4kXef/99goKC+N///sfx48czPPa3337jwoULuLm5GQmd9u3b4+HhQWRkJJs3b86v08hQ7dq1mTdvHj179lSteBHJF+fOnePKlSsAbN26NVvHOByOXG23a9cuRo4cCUC/fv3STbq/+eabVKtWDafTSc+ePTO8gygzXbp0ITExkejoaC5evMi5c+c4e/as8RgyZAgAvXv3TrX933//5eLFi9hsNuNupsJGiXkRERERERERyVPFixdn+vTpnDx5kgkTJlCuXDmcTidLly6ldu3azJ8/P93jXGVsGjVqRIkSJQAoUqQI9957L5Ayk7IweOyxx/jkk09yvZ69iEh6tm3bZjx/9913GT9+fJbHJCYmGsdWrVo1zaNfv34AJCQkZNnXX3/9RceOHUlISCAoKIhPP/003Xa+vr58++23WK1WoqKiaNeuHdu3b8+y//DwcK5cuUJ8fDxOpzPL9llJTk4mPj6eK1euEB4enit95gb9jyEiIiIiIiIi+aJ06dKMHj2aEydOMG3aNPz8/IiPj6dv375GyZpruRLvO3fuxGq1Go8tW7ak2i8icjv58ccfAWjWrBlBQUG8+uqrPPXUU5keExsbC0B8fDx///13msf58+dTtcvIrl27aNGiBREREZQoUYLVq1fj5+eXYfu6desyb9483NzcuHr1Km3atGHq1KmZjlG2bFmKFi2Kt7c3bm5umEymDB/vvfceANOnT8+wjbu7O97e3hQtWpRSpUoRFRWV6fj5RTXmRURERERERCRfmc1mBg8ezH333cc999xDVFQUL730Ep06dTLaHDlyhL/++gtIme2Y3izOf/75hwMHDlCrVq18i11EpCDFx8fz3XffARAaGkr79u3p1KkTe/bsAeDSpUscOXKE4ODgVMf16NGDHj163NDYM2fO5NlnnyUuLo7AwEDWrFlDlSpVsjyuW7dufPHFFwwaNIj4+HiGDBnCmjVr+Oyzzyhfvnya9v369cPDwwOLxYLVas30bqSNGzeyY8cO6tatywMPPJBuG4fDQUJCgvHIj3VIskOJeRERERERERHJE0899RS7d++mQYMGTJ8+Pc3+kJAQhg4dyttvv82xY8e4cOECJUuWBP6vjE1gYCARERFp6reXKVOGf//9l+XLl+drYt5VAuHgwYMZtrHb7cafO3fuTLeN6/jCUlJBRG4OH3zwAVevXsVisdC5c2cCAwPZsmULY8aM4dNPP+Wff/4hJCSEqlWr0rhxY2rWrEmFChUoXbo0fn5++Pj44HQ6cTgcHD9+nJiYGJKSkoiOjiYqKoqrV69y9epV7rvvPqpVqwbAmTNnmDRpklGGpkSJEnzyySc4HA527tyJn58fwcHBma6z8eSTT1KiRAkef/xx4uLiWLFiBWvXrmXAgAGMHTuWsmXLGm1nzpyZ7Z/H0KFD2bFjB/fccw/vvvvudf5UC4YS8yIiIiIiIiKSJ86dO8eePXsyrVkcEBBgPL92FqOrTE2rVq3STfa0atWKr7/+muXLl/PKK6/kYtSZO3nyJJAyUzUjc+fOxd/fn6ioKLp06ZJlf40bN87NEG9p586dIzAwEKvVWtChiOQ7h8PB0qVLAejbty+BgYEAWK1WPvzwQ55++mmmTp3KokWLOH78eKaLa2fliy++yHBfREQEjz/+eKpthw4dIiQkJNM+O3fuzO7du+nduzd79+4lMTGR2bNn07Nnz1SJ+awcPHiQrVu3Eh0dzapVqwAoWrRoto8vLJSYFxEREREREZE80bBhQ1auXMnBgwfZs2cPDRo0SLU/OTnZKMlQtWpVihQpAkBYWBg7duwAoHXr1un23bp1a77++mv27NnDuXPncpTUuRFxcXEAvPLKK6lK71wrLCwMp9NJQECAcR7/tWLFCsaPH2/0dzPYsGEDu3btonfv3pQpU6ZAYhg8eDCHDx9m3LhxPP7443h4ZD+1FRsbi9PpxGq15ug4kcLC3d2d3bt388EHH/DII4+k2R8UFMSHH37IBx98wK5du9ixYwd79+7l9OnTnDt3jkuXLhEfH09CQgIOhwMANzc3PDw8cHNzw2w24+HhQY8ePejfvz+QMlt+2LBhXLx4kf79+9O/f/9U75+DBw8SGhpKdHR0ts4hJCSE3377jSlTpvD222/z2WefGQt6Z1dgYCDPPvtsqou+zZo1y1EfhYF+C4mIiIjkwNKlS+nYsSMWiyXTdqtWraJJkybGLBYREZHb0aBBg5g0aRJXr17lwQcf5N1336Vr1674+Phw9OhRXn/9daPUy4svvmgc98MPPxglXtq0aZNu366EvdPp5IcffuDpp5/O47NJrXLlyjRq1CjdfWvWrCExMRGz2Zxhm8xK4RRWK1as4MMPP+SVV17h8OHD6daWTkhIICoqCqvVisViyfQzk9PpxG63ExcXh8ViwcvLK9Pxf/zxR2N27FtvvUWbNm1ydIHgjjvuIDY2luXLl9O5c+dsHydSmLi7uzNq1Kgs2zRp0oQmTZpk2Gbnzp00btyY7du3Z/h7CqBRo0bUqlWLxMREatased1xX8tsNvPCCy8waNAgfHx8cnx8qVKlePLJJwkLCyMoKIg2bdpw//3350ps+SnjyvkiIiIiYoiPj6dJkyb873//4/nnn8+ybZ8+fShbtixDhgzJ9hgHDhygZcuWGS5aJCIicrMpVaoU3333Hf7+/kRERPDkk08SGBiIl5cXderUMerIDx06NFVi3VXGply5cgQFBaXbd6VKlbjzzjtTtZe85aov3blz5wwXfNy8eTN33HEHAQEBWK1WTCZThg83NzcsFgtFixZlyZIlmY595coVnnrqKeP1HXfcQURERI7i9/PzA6BYsWI5Ok7kdhcUFJRrSflrXU9S3uWzzz5jyZIlTJgw4aZMyoNmzIuIiIhki5eXF507d2bHjh1MmzaNtm3bpnv7KMC8efO4fPkyVquVoUOHZnsMm83Gpk2bMq2P+MYbb7Bw4cIM91etWpWVK1dme0wREZG81rZtWw4cOMBHH33E2rVrOXnyJElJSZQsWZJ77rmHp556KlW5mpiYGH7++Wcg4zI2Lq1bt2bWrFls2LCBq1ev4u/vn6fncju7cuUKu3btAqBXr14ZtjObzZQuXRp/f3/8/f3x9fXFzS39eaHJycnEx8cTHx+faq2B9AwaNIhTp07h5eVF5cqV2bJlC/Xr16dv37689dZblCtXLstzcJXfcJVMEhEpSErMi4iIiGTT6NGj+eGHH9ixYwfDhw+nU6dOmM3mVG2SkpJ47733gJTas9WrV892/64F7zK75fvChQscPXo0w/36oikiIoVRhQoVmDx5crba+vr6YrPZstV25syZzJw5M8t2rrI4cv1++uknHA4HJpOJyMhI5s+fb+xLTk7Gbrfj6elJnz59OH/+fK6OPX36dBYvXgzAtGnT6NmzJx988AFvvvkms2fP5ptvvmH06NGMHDnSWBTWarWSlJTEjh07jLUN3N3dgZR/YyIiBU2lbERERESyyc3NjUmTJjFixAh+++23NEl5SEkQnDhxgmrVqjFixIgc9e/qL71+r40BUurtOp1O47Fhw4YsjxUREckL48ePx2q1pnoMHDiwoMPKsYEDB6Y5j/Hjxxd0WIXG119/DaRc5Bg4cCB9+vQxHv369WPAgAG8/fbbuT7uzz//zLBhw4CUhV/79u2Lh4cHo0eP5uDBgzz44IPEx8fz+uuvU716ddasWQOkJOEdDodRvkZEpLDRjHkRERGRa1SvXp2IiAjMZjOenp54enqme/v1Dz/8kO7xZ8+eBSAyMpLatWun2nftAmfPP/88o0ePTrXfNYvLdZt1eqKjo4GM6zG6+hAREckvDocDh8ORapvdbi+gaK6f3W4nISGhoMMolC5cuGAsuvrrr79Sq1Yt5syZw/PPP0/Lli1ZunQpdrvd+HtPSkrKUT3qfv36MWbMmDTbN2/eTNeuXbHb7bRv354pU6ak2l+pUiVWr17NF198wYsvvsg///zDuHHjaNeuHVarlbi4OOOORBGRwkaJeREREZFrXL16lYsXL95wP5cuXeLSpUsZ7k/vFn3XBYCM6rACRmylSpW6wQhFRERuTP/+/enfv39Bh5FrZs+ezezZsws6jELp7bffxm63c++999K8eXPg/0rvuRZvvZaHh0empff+yzXx4Fo//PADPXv2JDY2loYNG7J48eIMJy8MGjSIpk2b0q9fPxYtWoS7u7tR0kaTFkSu39KlS3nqqafYunUr1apVK+hwbjlKzIuIiIhcY/ny5QQEBBAYGIjFYsHT0zPTGew5YbPZiI+PJywszJjx/s477+Du7o6npyeXL18GICoqig8//BCbzYbNZqN79+5Grfpjx44BEBISkisxiYiIyPU5ceIEO3fuTHefa+a43W7PsM2JEyfyLLbcdu+993Lu3Dn69etnbEtOTgYyLqNnNpux2+38+++/GU4oGD58OJMmTTKS6JAy2/6tt95i/PjxJCcn07BhQ5544gmqVauGl5cXXl5emEwmo31CQgKxsbHMmDGDPXv2GNtdba5tKyI5c+XKFYoXL66SUHlEiXkRERGRa7gWB8sLrnq1184qmzx5MpGRkanaXbx4kRdffNF4Xa9ePapXr87evXv566+/AGjdunWqY1xfOs+ePUtMTAy+vr4kJycTGxurD9IiIiK5yNvbG0iprZ9RDfq5c+fi7+9PVFQUXbp0yVZ/hdljjz3GY489lmpbYmIiQIalYiwWS7ZLGl07q33z5s1MmjSJ5ORkmjVrxooVK/j+++8JCwvLtA9XPCL5IT4+nitXrlC6dOmCDiVPhYaGEhoaWtBh3LKUmBcRERFJx5UrVzh+/Hi22taqVcu4nTs9kydPZvXq1TRp0iTNF/ju3bvjdDoxm83ExMQwa9YsihQpQp8+fYwZ8+XKlcNutxsLn913331p6tcXL14cgL///jtVIr5Tp04Z1sMXERGRnLvzzjsBmDVrFjVq1Ei3TVhYGE6nk4CAAHbs2JFum4MHDxIaGmr0d7Nx1eO/drb7tXJS2/3axHyrVq3YtWsXU6dOZeLEiVitVrp168b9999vzJh3lf1zOp3Ex8cTFxdHsWLFbuBs5GYRERHBu+++S9++falTp06BxfHZZ5/x5ptvMnLkSIYOHUqRIkWyfazNZiMpKQmz2Zzpdwi59RXaxPzZs2c5fvw4ly5dwuFwGDXLgoKCuOOOOwo6PBEREbnFbdq0ia5du2ar7dmzZylbtmyG+0+cOMHPP/+cpv4qpHyodzl+/DizZs0iMDCQTz75xNjucDjo378/27Ztw2QyMWHChDT91KhRg2effZZt27YRExNDUlISTqeTunXrZuscREREJHtcd6nVqFGDRo0apdtmzZo1JCYmYjabM2zz3/4Ksz/++IPffvuNEiVK4O3tjbu7O4cPHwZSFrxfv349drud2NhY7r//fooUKZKjBYCdTmeq1yEhIak+C/n6+uLr65vusV5eXvj6+mqR15vY7NmzeeKJJ9Ld169fv1RrP2zfvp3JkyczefJk5s6dS58+fdI9Ljw8HIvFgsViwWq1Zvo+S0pKIj4+HqfTib+/f5bxhoeHM378eKKjo5kwYQLNmzenRYsWWR7n0q1bN1atWsULL7zA5MmTje05+TnIraFQJeZ/+eUXvv76a1atWsWFCxcybFe8eHHatWtH586deeSRR7SQh4iIiOQ615c7q9Wa7i3oNpuN5cuXA/93C/rhw4eNWvAnT56kYsWKQMoXxmvb5VRUVBTFixfHw8ODN954g6ZNm6bb7uOPP76u/kVEREQys3PnTgYPHpzuvrVr17J27Vrj9YEDByhSpEiOSss4HI4025xOJ1u3buX8+fNGGZ3Vq1cza9YsHnnkEXr27AmklBQpUaIEjRs3ZtCgQXTv3j0npyaFiLu7e5q1nf67hsH27dsBKFWqFD169Ei3n6SkpAzXNcjMk08+yYwZM7JsN3jwYKKiogAIDAw01onKLtfdrf+9y8Pd3T3NDPrk5OQcXeSSm0uhSMyvWLGCcePGsW/fPuD/rpS6ZslbrVZiYmK4dOkSycnJRERE8PXXX/P1119TpkwZnn/+eZ577rlcW5hNRERExPWhOCAggEWLFqXZHxYWZiTmXV8Yrp1hExAQkKavjBZHy4zD4aBYsWK8/vrrPProo9SvXx+Hw6GJCSIiIpJvgoODGTJkiFFKxt3dna+++orTp09z//3306RJExISErh48aKRdHQl5ps3b57h55aIiAjg/8riXOvrr7+md+/elClTxkjM//HHHyxZsgQPDw8jMX/w4EFiY2P55ZdfePvtt3P93CX/vPLKK4wbNy7TNuvWrQNS1j3I6LO1yWSiZMmS+Pn54e/vj7+/f4Y5Q6fTic1mIz4+njJlymQZ42effWZ8B2jYsCG7du3i4Ycfpnnz5nzwwQdZ3iEDGLH8t/xNnz590twBsHHjRlq1apVln3JzKtBMdlhYGM888wzff/89TqcTk8lE27ZteeSRR2jZsiVVq1Y16oZByhWvP/74g61bt7Jo0SK2b9/OuXPnGDlyJDNnzmT69Ok0b968AM9IREREbhU5qffo+nB97Qf+G7md2ul08vvvv/PNN98wd+5cTpw4Qf/+/Y0vAdkRHBxs3GIuIiIiciOaNWtGs2bNUm376quvAHjiiSeMJLmL3W43Jl1mZ82e2NjYNNs6dOiAu7s758+f59ChQ1SvXp0HHniAMWPGsGnTJqPdgQMHALjrrrto0qRJzk5Mbirh4eH8/vvvQMqEl/nz5wOwf/9+7HY7JpOJv//+m9DQUMLDw3N9/P379zN8+HAg5d/9rFmzWL58OcOGDWPz5s00btyYXr16MXHiRCPJ/8ADD/Dzzz8zceJEXnzxReD/1lTIqDyT3D4KLDG/efNmHnvsMS5cuIDT6eTxxx/n1VdfJTg4OMNjPDw8qF+/PvXr12fYsGH88ccfvP766yxfvpwjR47Qpk0bJkyYwEsvvZSPZyIiIiK3ItcH5vj4+HRvab169WqGxwCpJhdk17lz54CUmvT169dPtb106dJUqVKFkydP4nA4qFKlSrp9nDlzhsTERDp06JDj8UVEROTW43Q6OXLkCNHR0Tfcl5+fH8HBwVy8eJEzZ84AGGX8rmU2m3E6ncYjvc9Fv//+OyVLlsxwnZ6iRYvSpEkTtm7dyrp166hevTp169alRIkShIWFceTIEYKDg9m7dy+APvvcBhYtWmRc8Jk0aVKG7bp163bdJSQzcv78eR566CFsNht169Y11onq0qULbdq04bXXXuPjjz9mwYIFLF++nDfffJNnn30WDw8PHA6HkvCSrgJJzM+ePZvBgwdjt9spV64cM2bMoF27djnup3bt2ixbtowVK1bw1FNP8e+//zJy5Ej++usvpk+fngeRi4iIyO3m6tWrDBw4ME/6Pn36NJs2bWLXrl38+OOPHDt2zNhXvHhxHn30UR5++GEqVKjA1KlTAWjatCnbt29n5cqVaSY0REVFcccddwAYt3yLiIhI3jh48GCG+1w1oe12Ozt37szx8bnpyJEj6SbPr9ehQ4fYv3+/kSBdt24dderUSbO45vLlyxk3bhwvvvhiugt0fvTRR3z33XcMHDiQt956yyiBc622bdsaifnnn38ek8lEy5YtWbx4MZs2bSI4OJjdu3cbba/lKqWTk1r3Uri57tJ45513ePrpp/n777+5++67cXd3Z86cObi7u9O0aVNKlCgBQM+ePY0LN1kJCQlh2bJl6e4LCwujdevWnD17lvLly7Nq1SpjDSlImfk+efJkHnnkEfr27cs///zDm2++Sbdu3bBarcCN3U2b1270d1F+/S67FeV7Yv7zzz/n2WefJTk5mSZNmrBs2TLjC+T16tSpE3fffTddunRh9+7dzJgxA5PJxLRp03IpahEREbldFS1alKVLl6bZfunSJf73v//dUN9Hjx6lb9++xuvSpUvz77//UqFCBY4fP55u3czmzZuzfft2VqxYkSYxP2fOHBISErjnnnto3LjxDcUmIiIi6XMlkENDQzNsM3fuXPz9/YmKikp3Efn0+ssrrpnys2bNokaNGtfdz8GDBwkNDSU6OjrV+jujRo1i06ZNzJ4920iIQsqkzH379jF58uQ0iXmn08mPP/5IXFwcW7duzXA28X333Qek1NlOSEjAYrHQqFEjFi9ezPbt23niiSfYt28fnp6etGjRItWx8fHxAMTFxV33OUvhsWzZMvbv34+Pjw9PP/00RYoUwcfHB0i5U9XX1xdPT08qVKhgHHP+/HmOHj2arf7/uxCry9GjR3nooYc4fvw4gYGB/PjjjxnWom/WrBl79+6lR48eDBo0iPLlyxuJ+cK4PlR2fpddT3+SffmamP/qq68YOnQokHIl84cffshR/dbMlC5dml9//ZWOHTuyYcMGvvzySypWrMiYMWNypX8RERG5PXl6etKyZcs028PCwm6477Zt21KlShUqVqzIqFGjqFSpEkFBQZjN5gwXs+rcuTMTJ07kq6++YsSIEcZ2m81m3NJ77XYRERHJXcHBwRw6dCjT0jBhYWE4nU4CAgLYsWNHhu1cpWHyQ40aNbK1MGVWwsPDWb16NQCffPIJ7777LqtXr6Zu3bosW7bMGGPAgAF8//337Nu3j02bNqVKnG/atIkLFy4A8NZbb6WZbe/SoEEDTCYT8fHx/Pbbb7Ro0YL//e9/tGrVinr16vHbb79hs9lo1apVmtIlSszfWsqUKcPgwYMpVaqUsWhqcnIyQIYLu7pmqS9cuJAePXqk22blypV06tTJSKBfa/HixQwaNIgrV64QGBjI7NmzadWqVapFkF3sdjtxcXH07duXH3/80dju+red0b/xgpSd32XZlZ+/y24l+ZaYX716NYMHD8ZkMnHfffflalLexWq1snLlStq2bcu2bdt49dVXady4Ma1bt87VcUREROT2kpSUlGabw+HIlb7Xr1/PnXfeCWRvcbSmTZtSqVIlDh8+zKpVq+jYsSMAr776KqdPn6Z169Y8/PDDuRKbiIiIpGUymQgJCcm0zZo1a0hMTMRsNudKMrwwmTt3Lna7nZCQEIYOHcr9999PixYtOH/+PC1atGDmzJn07NmT9u3bU65cOc6ePcvcuXNTJeZdi3bWr1+f9u3bZziWv78/b775JvXr16du3boAVKpUiUqVKgGwYcMGIG0ZG0j/85vcvBo3bpzmjlBXmaKMEvM5yTv+d0Z7WFgYY8aM4cqVK5QuXZq1a9fi5+dnXFDKSHoLGRdW2fldJnkr56uSXadKlSpRrlw5KlWqxNKlS3M9Ke/i5eXFsmXLqFChAp07d+aee+7Jk3FERETk9hAeHm7MYL/2Ua5cuTRtXbN2/vs8M66kfHaZTCZjofsRI0Zgs9lYvHgxH3zwAWazmU8//TRH/YmIiIjkhKsO95gxY4zE3qpVq/D29sZms7F27VqcTifu7u488cQTACxZsgSbzQakrInjKoXz+uuvZzneK6+8QocOHQgICEiz74cffgBS7gb46aefmDhxYrolCOXWlJCQAGRcvz0ndd3/m5gvVaoUe/bsYciQIWzfvp1atWpRrlw5Tp06xYULF4iOjiY+Pt54XL58mXPnzvHaa69d/wnJbSffZsyHhISwa9cuLl68SNGiRfN0rBIlSrB169YMV/YWERERyS6r1Ur37t3TbI+Pj+fbb79Ntc315QBSZvD895bq3DJgwAAmT57M4cOH6datGxs3bgTg/fffz9XF3URERERcXDPQHQ4HtWvXplevXsa+hg0bsnDhQnbu3Mn48eON7aGhoaxcuZJhw4YZ22bMmEFsbCz16tWjc+fO2R4/Ojqa48ePc+zYMf766y/++usvdu3aBZCqjv/EiROv+xyl8Lp8+TILFiygZMmS+Pn5YTabOXDgAJAyIWb//v2YTCYSEhKoXr06QUFBxiLM2eFazPhaAQEBfPbZZ8ZrDw+PVDXsr2W1WvH29i7Ui7xK4ZOvNeYDAwMJDAzMl7GUlBcREZHcEBAQwOzZs9NsDwsLS5OYj4uLM2ZzRUdHG/Uvc5vFYmHWrFm0atWKVatWAdCtWzeee+65PBlPRERExJXwdnd3Z8aMGbi5pS7C0Llz5zSJ9jvvvJO9e/carxMSEpg8eTJApjOL4+Li6N+/P//++y9hYWGEhYURExOTbltPT0+qVq1KcHAwQUFBtGvXLt12drudyMhIoHDW+5bMRUZGprrAc63Lly+nuvvi008/JSgoyCh1kx2Zlak8evQoP/30k7Fu5qFDh/joo4/w9/fngw8+MNq1atUKm81Gp06dGDduXLbHlttXvibmRURERAojp9PJkSNHUi18dPDgQSDlS9zOnTvTHOP6Ygewa9cuo0zf9u3bCQ4OztMvfFeuXOGrr75KNbNn9+7drFmzhgcffDDPxhUREZHb0wsvvMDy5csBGDRoEA0bNsywra+vL1arFavVisViSfWZKCEhgfPnzwPw0ksvMXz4cJKTk42FM8eOHctLL72Et7c3J06cYM+ePcaxHh4eVK1alVq1alGzZk1q1KhBjRo1qFq1aoY1xiHlTsM//viD8PBwYmJicHNzo2TJkjf6I5F8FhAQwFNPPYWXlxdWqxVPT082bNjAr7/+SpkyZWjWrBlOp5PAwEAqV64M/N/drC+99FKGiXJXTfhr73y91rlz54xFTdu1a0dQUBBXr17lyy+/pFSpUkZi3ul08scffxATE8Ojjz6am6cutzAl5kVEROS2d+TIkQxLwFy6dCnNQlP/dd9996V6fejQoVQLKWV3odhrk/3piY2NZebMmYwfP56IiAjMZjNPP/00K1eu5MSJE3To0IFatWrRp08f2rZtS61atdLUyxQRERHJqeHDh7Nt2zZ27txJv379Mm3rqiWf0SQFV4UDm82G0+nE4XCQmJhIQkJCqgVbhwwZwt69e2nYsCF16tQhJCTkutYrrFWrFjNnzjRed+/eHS8vrxz3IwWrRIkSTJ06NdW2f/75h19//ZXatWvTs2dPPD09U01Scc2Yd10MykxGi7aWLVuW+vXrs3fvXtavX09QUBANGzakWLFihIWFceTIEYKDgzl58iQxMTGYTCb69u17A2cqtxMl5kVEROS255opP2vWLGrUqAGkzIIfOnQoxYoVY82aNUbbv/76i0uXLvHHH38YX/I2b96Mp6cnBw8eJDQ0lOjoaP7++29+//13nE6nUW7Gx8cnzdjHjx9n8uTJuLu788svvwCpF6r6559/+OWXX1izZg0//vij8aWhUaNGfPHFF9SpU4eJEyfy0Ucf8cEHH3DgwAFGjhxpjHfXXXfRsGFDpk6dqtu2RURE5LqULVuW999/nxYtWmT5eeLa5PqNCA0NJTQ09Ib7efTRR1m9ejV33XUXrVq1olOnTrkQnRQGrjsqMqr7vnXrViBlkkx6k1UiIiI4ceJElpNwHnzwQfbu3cu6desYMmQI7u7utG7dmu+++46NGzcSHBxslGyqW7cuZcqUuZHTktuIEvMiIiIi/1+NGjVo1KgRAGfPngXAbDYb2yAlCT98+HDjda1atWjWrFmavkqWLMkzzzzDhQsXjG0tWrRI065SpUp89913REREGNvatGkDpHyJGDp0KKtXrzb23XXXXbz88sv07t3b+GJssVgYNWoUw4YNY9asWcyaNYvff/+d2NhY9u7dy9tvv62kvIiIiNwQq9Va0CFclzJlyrB27dqCDkNyWVhYmFF68tChQ7Rq1SrNwqt//PEHr732GsWLF2fGjBlp+li5ciVPPvkkXbt25d133yUoKCjdsdq2bcvbb7/Nhg0bSEpKwsPDg1atWvHdd9+xadMmnnrqKXbv3m20vZZr1n5O6t3L7UOJeREREZF0XLx4Md3tTzzxBPPnzyckJISmTZvSs2fPdNv5+fnxzDPPsGfPHoKCgrj//vt54IEH0rRzd3enbdu2XLx4kerVq9O0aVO6du1q7Fu0aBG1atWiTp06DBgwgI4dO6ZZbM3F29uboUOHMnToUA4fPsyqVav4+++/ad++/fX9EERERERECqFFixYZz7ds2cKJEycYM2ZMqjYbNmxg+fLlWCwW3n77be64445U+9esWYPT6WTdunV89tlnGY7VuHFjPD09uXr1Ktu3b6d58+bGxJ3t27cDsGPHDoA0iw/Hx8cDKQsai/yXEvMiIiIi6Rg0aBCDBg1Ks71YsWL8/vvv2erjtddey1a7BQsWZLjPz8+P48ePZ7qoWXpCQkJS1bkXEREREbkVOJ1OvvjiCwCGDh3Kpk2bOHDgAC+88AJeXl48+eSTAPTp04dRo0aRkJDAtGnTeP31140+YmNjjbtShw4dSunSpTMcz2q1UqtWLfbs2cMvv/xC8+bNqVWrFmvWrKFVq1bY7XZ27NiBl5dXmjtplZiXzBSKxPzx48fx9vbGYrFgNpvx8PDA3d091S3XTqeT5ORkkpKSjEVBHA4H5cuXL8DIRURERPJeTpPyIiIiIiK3qiVLlnD48GHMZjMjR46kVatWjB07lqNHjzJgwAD+/PNPPvjgA4oVK8YjjzzCwoULmTdvXqrE/LJly4iNjcXLy4sXXnghyzGHDRuG2WzmvvvuA1JKSbruSt26dStxcXG0a9cuzQLF69evz8Uzl1tNofiWFxQUdF11T+vWrWss9CAiIiIiIiIiIiK3roSEBEaNGgWkzIgvX748f/75J6+88gpjxozh7NmzbNq0icuXL1O8eHEGDBjAwoUL+fvvv9m+fTv33HMPANOmTQPgqaeeSlPiJj39+vXLcN8PP/wAQKNGjdi2bRv79+8nJiaGESNG3Ojpyi0u/QKlBcDpdF7XQ0RERCS//PDDD9SrV48//vijoEMREREREbntjB49mhMnTuDl5ZVqBryfnx9vvvkmvXr14tdff6V48eIAtGrViqZNm/LOO+9QqVIlAPbs2cPWrVuxWq2MHDkyR+MnJiZy9OhRVqxYwaRJk3jqqaf46quvABg/fjz33nsvQ4YMYePGjblzwnJLKxQz5gFMJhMlS5bM9FbtpKQkwsPDMZlMlClTJltXtERERERyw7Jly3jssceMknsiIiIiIpK3nE4nR44cITo6mjVr1vDxxx8DMHjwYMLCwggLC8NutwMQGBjIs88+y6FDh1L18eGHH+Ln52fkEd955x2jj1KlSmU6/pgxY9i5c6cx1qVLl9Jt5+bmRsWKFbnrrru46667aN26dYZ9hoWFAVxX9RC5tRSaxDzApk2bCAoKynD/kSNHqF69OgBnzpzJr7BEREREmDp1KhaLhR9++IEaNWoUdDgiIiIiOXLw4MECPV4kK+PHj+fdd99Nta1Tp0589913adp+9NFHfPTRRwDMnTsXf39/oqKi6NKlS4b9ly9fHk9PT06cOAHAt99+y8qVK3E6nSQlJREfH8+9997LsmXLjGPsdju//PJLmn5q1apFzZo1qVGjBjVq1CAkJARvb+8Mx542bRozZ87EZrPx559/AqRZcHbevHkMHDgw1bbk5OQM+5SbX6FKzGdFV5JERESkoCxatAibzUaZMmUKOhQRERGRbPPz8wMgNDQ0V/sTyW0OhwOHw5FqW3x8PJCS2P7111/ZsGEDc+bMISAgwGgTFhaG0+kkICCAHTt28Mwzz3DgwAEsFgsWi4WkpCQuX76MzWYjOTk51ef5uLg4HA4HSUlJJCQkkJiYmGr8xx9/nLCwMJo2bUqdOnWoWbNmqrGz65577uHpp582XgcFBRn17q89/4SEhBz3LTevmyoxLyIiIlJQihUrVtAhiIiIiORYcHAwhw4dIjo6+ob78vPzIzg4OBeiEvk//fv3p3///unu27lzJ6tWraJevXpG+Zr/lp9Zs2YNiYmJmM1mGjVqxK5du9L00bhxY1auXEmjRo1yFFuDBg2YP39+jo5JT506dejevTve3t7cc889PProo2kucmX2c5BbkxLzIiIiIiIiIiK3KJPJREhISEGHIZIrsqoJX5gtWrSooEOQQsatoAMQEREREREREREREbmdKDEvIiIiIiIiIiI3hZMnTzJ37lz2798PwL///sv48eMLOCoRkZxTKRsREREREREREclzYWFhDB8+PMP9NWrUYMyYMTRr1gy73Y6npyfu7u7G/k8++YTNmzczdOhQXnnlFapUqUKXLl3YtWsXiYmJvPnmm/lxGlJIJSUlFXQIIjmixLyIiIiIiIiIyG3s0qVLXLp0CW9vbzw8PHBzu/4CCw6Hg6SkJGJjY7njjjsICAgw9sXHx7NgwYIMj+3QoQMAx48fJyYmBi8vLywWC//++y/JycmUK1eOxo0bA7B161bat2/Prl27aNu2LYMGDbrumOXmZrPZcHNzIyYmpqBDEcmRfEnMnzt3jlOnTmGxWLBYLMYVTzc3t1S/7M+fP4/Vas20H5czZ87gdDrTbZecnExSUhKJiYnGw2azcd999+XeSYmIiMgt5+DBgwV6vIiIiEhB+Prrrxk2bFiu97t48WK6detmvLZYLAA0a9aMhQsXGtu3b9/OY489ZuSEwsLCjH02mw1fX18qVKhAsWLF8Pf3x8/Pjw0bNgAwduxYxo8fj8lk4uLFixQvXjzXz0MKrwMHDhATE4O/vz8+Pj4FHY5IjuRLYn7RokWMHDky0zZOp5M2bdpkqz+n08mdd96ZoxhMJpNuaREREZF0+fn5ARAaGpqr/YmIiIjcDNzc3PD29sbHxwd3d/dU5WOulZCQwMWLFwEoW7Zsmv1OpzPVjHmTyZRqv6enJ5CSoC9XrpyxvUSJEgCYzWYgJRl/4MABGjZsyJ9//onD4aB+/foAeHh4cN9997Fq1SomTpzIiBEjAJg9ezZvvPEGu3fvJjAw8EZ+HHITKVeuHEeOHAH+79+PyM0i30rZZDS7PadtrqetiIiISGaCg4M5dOgQ0dHRN9yXn58fwcHBuRCViIiISP4YMmQIQ4YMybLdxo0badWqFe7u7pw9ezbH47gS8xnx8PAgKSmJHj16sH79en788Uc2bdoEQLt27Yx2Xbp0YdWqVZw6dQqAb7/9lgEDBuBwOBg7dizTp0/PcWxycypatCi+vr4kJiYWdCgiOZYviXlvb29KlSqFh4cHZrM5zWPXrl2YTCZq166daSkbm83G/v37MZlMNGrUKMN2SUlJ2O12EhMTiYuLIzIykri4uLw4NREREbkFmEwmQkJCCjoMERERkVtaVpUMXGWJTSYTsbGxdOjQgeLFi+Pu7k7nzp2Ndo888gjDhg1j5syZBAQE8O677+Lh4cGECRN48cUX8/o0RERyRb4k5p9++mmefvrpDPe76sx/8803BAUFZdju6NGjxpfm7du35ygGXTkTERERERERESk4WeVmEhMT8fb2ZunSpQwZMoRp06YRHR1N165dU5XOCQwM5PHHH2f27Nm88847lCpViiVLltC0adO8PgURkVyTb6VsClpWt0uJiIiIiIiIiNzuXLPa3d3d09SIv1EJCQkAHDx4kN69exvbw8PDU+03mUw8+eSTfPHFFyQnJ7Np06Y0aw3GxsamKn2jpLyI3GzcCjoAEREREREREREpeAcOHDDKDi9ZsiTX+3fNmA8LC2PBggXGY/369cD/JeZPnjxJp06dSE5OJjQ0FG9vb5KSklI9LBYLH3zwAWazmY8++ohevXpx9erVXI9ZRCSvKDEvIiIiIiIiIiL4+fml+zy3VKtWDafTaTy++uorAF5++WWcTifr169n27Zt3HvvvYSFhVGjRg0++eQTzp49m+7jueeeY+HChXh6evL1119TvXr1PLmgICKSF5SYFxERERERERERPDw80n2eE0lJScTExBAREZHjY48cOcL999/P+fPnKVWqFCtXrsTHxyfTY/73v/+xadMmKlWqRHx8PJUrV76uuEVE8tttU2NeREREREREREQydm0y3t3dPcN2Docjy/rz9957L1u2bEm1zWazERYWhpeXF3fccUeaY4KDg1mzZg29evVizZo1NG/enLNnz2YZd8+ePTlw4ADHjx+nTp06WbaXm8/Bgwcz3Ge3240/d+7cmaNjRQqSEvMiIiIiIiIiIpIjVapUSXe7w+HAbrenWwpn9+7dNG/enA4dOrBq1ap0j2/RogXHjh3Dy8sLLy8vTCYTPXv2TLdtREQE69atw9PTEx8fHyXlb0Guf0ehoaEZtpk7dy7+/v5ERUXRpUuXLPsSKSyUmBcRERERERERkWxzd3fn+PHjOT7OlRj18vJKtX327NmsXr2a2NhYXnvtNXr16mW0c3NzY/78+en2t2XLFtatW4fZbM5xLHJzCA4O5tChQ0RHR2fYJiwsDKfTSUBAADt27Ei3jZ+fH8HBwXkVpsh1KVSJ+ePHj5OUlJTh/n/++cd4fvjwYaxWK5UqVcqP0ERERERERERE5AZ4enoCaRPz586d49y5cwCpErBZlcuRW5/JZCIkJCTTNmvWrCExMRGz2UyjRo3yKTKRG1eoEvOdOnXKso3rl3LNmjWpW7cue/bsyeuwRERERERERETkBrlyOv+tXz927FjGjh1LbGws3t7exva4uDiSk5Pp3bt3uv25Fph11RgXEbmZFKrEvNPpzNP2IiIiIiIiIiJSuJhMJnx8fPDx8Um1PT4+HqfTyYIFCzI9PjExMS/DExHJE4UiMV+lShV8fHywWCx4enri7u6Om5sbJpMJNzc3nE4nTqeT5ORkHA4HiYmJ2Gw2KlSoUNChi4iIiIiIiIhIHjh9+jQ//fQTZcuWpUaNGqn2HTx4kHnz5jF48GCVORaRm1KhSMwfO3asoEMQEREREREREbnlOJ1Ojhw5kunimS6RkZHG88OHD6cqKwNw6tSpXI8vM8888wxTp05l0KBBTJ8+PdW+tWvX8t577/H++++ze/du6tWrl6+xiYjcqEKRmBcRERERERERkdx35MgRqlevnuPjhgwZkgfRpC88PJzZs2ezdu1a7rrrLsaNGwdAly5dmDp1Kt9++y2ffPIJFovFOOaXX34BoH379krKi8hNSYl5EREREREREZFblGum/KxZs9KUg7Hb7SQkJGC1WnF3d+fSpUt06NABgM8//5wGDRoYbQ8ePEhoaGiW49ntdhITE41HQEAAVqs1VZu4uDhWrVrFsmXLAJgxYwYzZswAYNiwYUa7+++/nzvuuIPw8HB+/PFHunTpAqTUnncl5l1JfBGRm40S8yIiIiIiIiIit7gaNWrQqFGjVNu+//57Hn744XTbZzZj3uFwYDKZsjXu4sWL6datG6dOneLrr782ti1evNhoc/fdd9O1a1e6dOlClSpViIiIwGq1YrVaGTx4MDabjdq1axvt169fT3x8PM2aNaNhw4Y4HA4SEhKIiYmhZMmS2YpLRKSgKTEvIiIiIiIit5T4+Hg2bdqExWKhVatWWbaPjIzkn3/+AaBevXq4u7vndYgihYrJZMLd3T3Tf/tOp5PExEQ8PT0zTco7nU6SkpJITk5Otf23337jrbfeMl43bNiQnj178r///Y/y5csb2+fPn0+fPn3S9Dtx4sQ027Zs2ZImFqfTmWFsIiKFyS2dmLfZbGlulxIREREREZGbn9Pp5PLly4SHh3PmzBmOHTvG4cOH2bVrF/v37ychIYFSpUpx5MgRAgICMu1r7dq19OrVC4CrV6/i5+eXH6cgUuA6duxIXFwcXl5eWbbduXMnjRs3ZvPmzWlm3qfH4XAQHx+Pp6cnAN26daNSpUrcfffdjBo1KlWZnGsFBARQq1YtY8a86/jM2Gw24yEicrMokMT81atX8ff3z/Nx3n33XUD1xkRERERERG4Wx48fZ+TIkdjtdpKSkkhKSsJutxMXF0d0dDTR0dHExMQQExODw+HItK+wsDAef/xxVqxYkelM4GsndGlyl9xOzGYzZrM5zfbjx4+zevVqBgwYgLe393X17e7ujq+vb6rXBw8ezPIiQKdOnejUqdN1jSkicjPJ18R8dHQ006ZN4/PPPzduE8wrNpuNL774gvDwcI4fP84XX3xx3f+ZiIiIiIiISP6w2WzGgpDXMpvNeHp6YrFY8PLyokiRIpw7d46kpCR69uxJxYoVKVmyJCVLlqRUqVKUKVOG0qVL4+vrm2VpGovFAqSU8/hvkvKHH34gKioKDw8PIiIiuHjxIhEREWmeX758GR8fHwICAqhRowa9e/emZ8+eufeDEckHdrudyZMnM27cOGw2G/fccw8NGzbMtf6zMzNfROR2kW+J+eTkZKpWrcrFixeBjMvMNGvWjMuXLxMUFES1atW46667qFu3LrVr1073Km5GPvnkE8LCwoCUmmNJSUm5cyIiIiIiIiKSZ1xlKxo3bszatWuxWCxYLJZ060j7+PiQnJzM7Nmzc/R98b9cifv0EvhffPEFq1atylY/UVFRREVFcfr0afz9/ZWYl5vK7t27GTBgAPv376dYsWJMnz49V5PyIiKSWr4l5t3c3GjWrBnLli3DZDJx5swZqlWrlqZdQkIChw8f5siRI6m2m81mqlevzt13303btm154IEHMiyHc+bMGd555x0g5YPVvHnz8qV0joiIiIiIiNwYV3Lcw8Mj09rw586dIz4+ngoVKtxQUh5Svq9e++e1qlWrRosWLfD09Ey1/9KlS+zatQuAli1bYjabcTgcJCUlkZCQQMWKFW8oJpH89OWXX/LUU0+RnJxMjx49+PjjjylZsmRBhyUickvL11I2DzzwgHFLYkaJeUi5fdDX15fo6GhjW2JiIvv27WP//v3MnDkTDw8PmjZtyiOPPEJoaCg+Pj5AyqyJ/v37c/XqVUwmE6NGjaJ58+Z5f3IiIiIiIiJyw1zJ77179xIcHJxhu4SEBADCw8MzbWe324mPj+e+++5j0aJFADz88MNs3boVq9WKu7u70ZfdbqdKlSo4HA6jrv3XX3/Nhx9+mKbfjRs30qpVKwAWLlxIqVKlru+ERQqBf//9l6CgID744AM6duxY0OGIiNwW8jUxf9999xnPz5w5k2nbhQsXct9993Hs2DH++usv9u7dy86dO9m7dy/R0dHY7XZ+/fVXfv31V8aNG8fQoUN59tlnGTduHBs2bMBkMtGmTRvefPPNvD4tERERERERySWukjWJiYnExMRk2M61z2w2Z9rOlZiPj483tsXHxxMREZGmrdPp5MSJE6m2ZbXArMit4LXXXuO1114r6DBERG4r+ZqYDw4Oxt/fn+joaM6dO5dle19fX+rVq0e9evXo3r07kFKrftu2baxatYqlS5dy7NgxLl++zPjx43nvvfew2+0AVK9encWLF6d7K6KIiIiIiIgUTq5EeJUqVTh69GiG7caMGcO7777L6NGjefnll3M0xmeffYaHhwdFixbF09OTzZs3065dOywWC3FxcUZJmtjYWPz8/G7ofERERETSk+9Z65o1awJw9uzZ6zreVat+woQJHD16lPXr11OmTBmcTieJiYk4nU6sVitr1qzJtB6hiIiIiIiIFD6uxLy3t3em7Y4dOwZAUFBQjseoUqUKFStWxN/fH6vVmmphWTc3N8xmM15eXhQvXhyLxZLj/kVERESykq8z5iFlJvu2bdv4999/b6ify5cvs2jRIqZMmcK///6LyWTC6XRiMplISEhg5MiRLFiwINUHLBERERERESncbDYbgLGOGKRM8EpKSkrV7vTp0wAMHz6cV199NcP+XnrpJQYOHJgHkYqIiIhcv3xPzJcvXx6AsLCwHB136dIldu/eze7du/n555/ZsmULSUlJOJ1OAGrUqEHPnj15++23iY+P55tvvqFEiRJ8/PHHuX4O6UlKSiI5ORlPT898GU9ERERERORWFBcXB6SeMX/q1KkM68i7EvQZyaz+fGYiIyNZsWIF/fv3v67jRURERDKT76VsypYtC8CFCxcybffNN98wePBgWrduTfny5SlRogQPPvggr776Khs2bMBut2MymWjbti3Lli3jwIEDjBkzhh9//BEfHx+cTidTpkxh5syZeXIeUVFRvPXWW9SrVw8fHx/MZjMWi4WyZcsyePBgTp48ma1+fvjhBzp27EiJEiWwWCxUq1aNsWPHcvXq1TyJW0REREREpDC7cuUKkDox7+XlBcDChQtxOp3ZerRo0QIgR6VonE4nCxcupHv37pQrV46RI0fm3omJiIiIXCPfZ8y7EvMXL17MsI3T6WT+/PnG82tZrVYaN27Mgw8+SK9evYz+XJo1a8b8+fN55JFHSE5O5tlnn+Wee+6hevXquXYOv//+O126dOHMmTNp9p0/f54vvviCuXPnMm/ePLp165ZuHw6Hg/79+xvn6XL8+HEmTJjAwoUL+fnnn6lcuXKuxS0iIiIiIlLYXbp0CSDVmmHu7u7X3Z/Vas10f2RkJFu3bgUgMTGRnj17AlC0aFG6du163eOKiIiIZCbfE/N33HEHkHI7YVJSEh4eaUMwmUwUL17cWJCnWrVq3HXXXdSqVYsaNWpk+aGsc+fOjB49mnfeeYf4+Hj69u3Lzp07cXO78RsETp8+Tdu2bYmMjARSPqx16dKFu+++m4iICL766itOnz6NzWajR48e7Ny5k/r166fp55lnnkmVlK9VqxYNGzbk77//ZtOmTZw8eZK2bdvy+++/4+/vf8Nxi4iIiIiI3Axc65GVK1fO2Ob6DvjSSy8xbty4bPXjKnHz33Kj8fHx/Prrr2zatImff/6Z3bt3k5ycDKR8Fw0NDaVbt260adMGs9l8o6cjUmgcPHiwQI8XEZHU8j0xf+2HojVr1qSaBQEQHR0NwIgRI2jdujVWqxVvb2+KFClCkSJFsj3Oa6+9xpIlSzh69Cj79u1j69atNG/e/IbjHzhwoJGUf+yxx/j8888JDAw09g8fPpzWrVuza9cuHA4HL774Ihs3bkzVx3fffcf06dON1x9//DHPPvus8Xrx4sV0796dEydOMHLkSKZNm3bDcYuIiIiIiNwM/vrrLyB1Yt7l/PnzN9x/XFwcXbp0ISEhAQA/Pz/q1KnDli1b8PT0ZMaMGTc8hkhh4ufnB0BoaGiu9iciIjcm3xPz1852z+y2wFGjRqXZZjKZKFq0KGXLlqV8+fJUrVqVmjVr0qBBA+rWrZuqraenJ2+++SY9evRg1qxZuZKU37BhA+vWrTNi//rrr9PM3vf19WXRokVUqVIFgM2bNxMeHm7cKZCUlMTLL79stB8xYkSqpDzAo48+yi+//MK0adOYOXMmY8aMoWLFijccv4iIiIiISGHnmpXr+k51rYULF9KjR49s9dOyZUs2bdqUZntgYCBdu3blzJkzDBkyhEceeYStW7fStm3bGwtcpJAKDg7m0KFDxkTIG+Hn50dwcHAuRCUiIvmemHeVk/lv7fjscDqdREZGEhkZyR9//IHJZDL2BQQEcP/99/O///2PLl26YLVa6datG4sXL+aRRx7JldinTJkCpNQo/PzzzzMsqVO5cmXq1q3Lvn37SE5O5vDhw0ZiftWqVcYMkGLFivH666+n28cLL7zA9OnTSUpKYu7cubz66qu5cg4iIiIiIiKFldPp5NChQwDUrFkzz8aZOXMmPj4+eda/SGFiMpkICQkp6DBEROQ/8j0xX7p0aRYvXkxgYCB+fn54e3tjsVhwd3fHzc0Nk8mE3W4nKSmJpKQkEhMTuXr1KlevXiU6Oprw8HD+/vtv/v77bw4fPszJkycBuHLlCkuWLGHJkiUUKVKE0NBQXnzxxVxLygO8/vrrPPzww5jNZkqXLp1pW19fX+O53W43nq9evdp43qNHjww/DAYFBdGsWTM2b97M2rVrlZgXEREREZFb3p49e7h8+TJFixalTJkyafY//vjjPP744zc8jpLyIiIiUtDyPTHv6+vL//73v0zbuBbeyc5irWfOnGHDhg2sX7+e5cuXEx0dzeXLl5k8eTKff/45P/30E02bNs2V2GvXrk3t2rWzbOd0Ojl69KjxumTJksbzPXv2GM/btWuXaT8NGzZk8+bN7NmzB6fTmeoOARERERERkVvNqlWrAGjUqFG6+81mc7a+JwIkJiZe153aIiIiIvkhe59o8tHu3bsxm814enry77//Ztm+fPny9O3bl7lz5xIeHs706dOpUqUKTqeTu+++O9eS8jmxdetWIiIiAChRogQ1atQw9v3zzz/G8yZNmmTaT506dQCw2WyEh4fnQaQiIiIiIiKFx/LlywFo3bp1uvvnzp2LzWbL1uO+++7Lz9BFREREciTfZ8xnpWjRosasBm9v7xwda7VaGThwIP3792fChAkF9kFs8uTJxvM+ffrg4ZHyY3Y4HFy6dAkAf39/o+58Rq6daX/y5ElKlSqVB9GKiIiIiIjkP6fTyZEjR4wFKQ8fPszvv/8OpKzbtXPnTqNtYmIiAMePH0+13cW1IGV6dxlnZ9a8w+HIcfyumERERESuR74l5pOSkti/fz8BAQFGTfn0uBLXkDYxX6ZMGXx9fbFarZjN5gz7cFm5ciUmk4m5c+dy11133fhJZMOWLVv4/vvvAfDy8uKll14y9sXHxxvPy5cvn2VfxYoVM56fPn06yxn2mZk4cSITJ07MVlvX34HdbmfNmjXXPabkHdeXgMTERP0dieQhvddE8o/ebyL5ozC915KSkrhy5YrxesqUKQBUq1aN+Pj4VOVBk5KSAHj11VdzvP7W7t27KV68eJrtcXFxRsnQb7/9Fkgpp5rdn8uXX35pPN+wYQNFihTJUVxyaytM7zWRW53eb5IXHnzwwTwfI98S85GRkRnWCcyI2WxO9TosLAyTyZSjOoEmk4nY2NgcjXu9bDYbgwcPNuIbM2ZMqgWLXLXzIXXSPSPXLkh09erVG4otLi6OyMjIHB3jdDo1C+QmoL8jkfyh95pI/tH7TSR/FIb3mr+/PwB79+5l9+7dADz00EPGdhfXd6lixYrh5eWVrb4jIiJITEwkLi4u3XM9fPhwmiR/+fLlM/25fPTRRxw/fpzLly8b3zNdk8cKw89TCif92xDJP3q/yc0kX0vZ5NbCO08++SQ+Pj5Gf8nJySQnJ+N0OklKSsLhcOBwOEhMTMRut1O0aNFcGTcrY8eO5dChQwDUqlWLkSNHptp/7Qz/7HyYvPbCxLWz7a+Ht7c3gYGB2Wp76dIlY+aIp6fnDY0reePa/2j0dySSd/ReE8k/er+J5I/C9F6z2+1ERUUREBBAcnIyDz30EH/99RetW7dOc3e0K+6BAwfSokWLDPu59jvUqFGjOHDgAA6HI91zrV+/Pr6+vsTExAAQFBTEM888k+nPpUWLFmzcuNF47eXlxeDBg7FarTk+f7m1Fab3msitTu83uVmZnPm0TL3NZmPp0qVGKZv/zoZ3iYiI4LHHHsNkMqWp8+fm5obJZOLMmTOpZqIXBitXrqRz5844nU6sVis7d+6kVq1aqdo4HA6j3ny7du1Yu3Ztpn2eOHGCKlWqAPDee++lSfTnleLFixMZGUlgYCAXL17MlzElZ9asWUNiYiKenp75cmuNyO1K7zWR/KP3m0j+KEzvtZ07d9K4cWN27NiR5d3VZrOZpKQkFi5cSI8ePa67n/9atGgRvr6+NGzYMMs1wAASEhIYOHAg1atXp3Hjxtxzzz1Kyku6CtN7TeRWp/eb3Kzybca81WqlZ8+eWbY7d+5cPkSTu06ePEm/fv2MGfyffvppmqQ8pMyY9/HxITY2lqioqCz7vbZ8TUJCQu4FLCIiIiIichOx2+150u9/k/xZsVgszJ07N09iERERkduLW0EHcLOLj4/n4YcfNhZMDQ0NZcCAARm2L1myJADh4eFZ9n3tQrgWi+UGIxURERERERERERGRwiBfa8yfOnWKxYsXU7p0aYoWLYrVajVKu7hEREQYzzdv3pxuXfr9+/djs9koXrx4mkWB8pPT6eSJJ55g3759ADRu3JjPP/8802PuvPNO/vnnH06dOkVcXBze3t4Ztr327gE/P79ciVlEREREREREJCN///23UVZXRETyTr4m5jdv3syoUaOybGcymQBo2bJlutsfeughY5vVaqVq1aoEBQVRo0YNmjZtStOmTfH19c29wDPw2muv8c033wBQrlw5vv/++yxnttevX58NGzbgdDrZsWMHrVq1yrDttm3bjOcVK1bMnaBFRERERERuIvPnz2fLli18/vnnuLnppm8pXK5evUrr1q0BGDp0KP379y/YgG7Qrl27aNKkCf3792fs2LE5StDb7XYSEhJwc3PLdBKiiIikyNfE/JEjR9KdAX8j4uPjOXDgAH/++SdLly4FUhaJrV+/Pt26deOxxx7Lk6T2Z599xvjx4wHw9vbm+++/p1SpUlke16pVKyZNmgSkLBibWWJ+y5YtxvOQkJAbjFhEREREROTmMmnSJIYPH07x4sX58MMP8fLyKuiQRNLYs2cPkLocbU7Ex8djs9nw9vbGw8MDd3f3TNuvXr0aAE9PTywWC2azOcO2/v7+VK9ePVtxOJ1OnnvuOZKTk5k1axbBwcGMGDEi2+fx8ccfM2LECOrVq8fevXuzfZyIyO0qXxPz/fr1o1OnTpjNZjw8PDCbzbi7u+Pu7o6bmxsmkynNA1JmyiclJWG324mLiyMqKorLly9z/vx5zpw5w5EjR/jzzz85duwYAA6Hg927d7N7925Gjx7NnDlz6N27d66dx/Tp0xk2bBiQchFgwYIFNGjQIFvHtmzZEj8/P6Kjo5kzZw5vvvkmPj4+adr98ccf/PnnnwCULVuWSpUq5Vr8IiIu8fHxbNq0CYvFkumFQoADBw4wbNgwLBYLa9euzacIRURE5HY2efJkSpcuzdq1a5WUl0Lp2qT49a4Nt2DBAgYOHJittps3b6Zv375ERkZmq/1jjz1m3OmflY8//pjt27cDKediMplISEjI9nm5SvAWK1YsW+1FRG53+ZqYr1atWp72HxkZyYYNG1ixYgVLly4lNjaWMmXK0L1791wbY/ny5QwZMsSY+f/+++/TtWvXbB/v4+NDr169mDZtGpGRkYwePZpPP/00VRun05nqqvSjjz6aK7GLyO3J6XRy+fJlwsPDOXPmDMeOHePw4cPs2rWL/fv3k5CQQKlSpThy5AgBAQEZ9mOz2di0aRNFixbNsM0bb7zBwoULM9xftWpVVq5ceUPnIyIiIreP7du34+/vT5EiRQo6FJF0XZuY9/T0vOH+XJMXXRMVAZKTk7Hb7QBUqFCBe++9lw0bNhAdHU2NGjUoXrx4mn727NlDTEwMVatWzda4v//+u1F6uG7duhw8eJARI0bw2Wef8c4779CjR49UMaXHtYag3q8iItmTr4n5vBYYGEi3bt3o1q0bn332GTNmzMBkMmV6W1dOJCUlMWTIEJKTk43xTp8+zfPPP5/pcY0aNaJnz57G6+eff56ZM2dit9uZMmUKVquV8ePHY7FYiIqKYujQoaxbtw5I+U/+mWeeyZX4ReTWcvz4cUaOHIndbicpKSnVnUXR0dFER0cTExNDTEwMDocj077CwsJ4/PHHWbFiRYa3zrq+aGQ2Y+bChQscPXo0w/36kC4iIiI5UaFChYIOQSRTrmQ0cN1rIPTp04eePXtmWJd95cqVdOrUCQ8PD8qWLcvy5ctp164dP/30EyNGjKBfv35pjilXrhwxMTHZmiB59epVevToQWJiIjVr1mTr1q2cOHGCwYMHs23bNnr27MnHH3/Mp59+SsOGDQF45513eO211+jYsSPLly8HML5H5MeafyIit4JbKjF/LV9f3ywT5jm1ZcsWzp8/b7yOjIzk448/zvK4fv36pUrM33XXXYwfP964Gv3BBx/w5ZdfUqVKFQ4fPkx8fLzRdsyYMdm+wi0ihZPdbsfNzS3LWpE5ZbPZWLZsWZrtZrPZqDfp5eVFkSJFOHfuHElJSfTs2ZOKFStSsmRJSpYsSalSpShTpgylS5fG19c30xhdFzkzu9jp+jLSpk0b1q9fb2zfuHEjrVq1yrULpXJ7y0kJpux4+umnjVloWfH09OTzzz+/4TFFRETk1mE2m43P/Ncjq1IxFy5cAKBixYrG53XXGncRERFp2sfHxxu5i6zqyyclJfHoo4/y119/4e/vz3fffYe3tzc1a9Zky5YtfPHFF4wePZodO3bQuHFjBg4cyHvvvYfZbMbhcKRbmldERLLnlk3M54UzZ87kWl8jR47E6XTy8ssv43A4iIqKSrM4yoABAxg3blyujSlyu4qKiuKjjz5iyZIlHDt2DHd3d+688046derEyJEjMy3NAhAXF0fx4sWJj49n9OjRTJgwIdP2TqeTr776ii+++IIDBw4QFxeHm5sbtWrV4plnnmHAgAFZ3gaaHa4Z7I0bN2bt2rVYLBajFuR/4/Hx8SE5OZnZs2dfd3Lc9SXg2llB/xUdHQ2Q4Qf03L44IbeuGy3B1Lt3b3bv3p1h/926dTMWcV+0aBFXrlzJVlyBgYFKzIuIiNwmBg4cyIwZM7LdPjQ0lNDQ0CzbRUVF4e/vn2a7zWbDarWm2e5Kst91113GtrJlywLw77//pmn/999/43Q6MZlM1KhRI8M4kpKS6NGjB+vWrcPT05Nly5alGsNkMjF48GA6dOhAv3792LBhA1988QUPPfSQEWdulO8REbldKTGfA3369KFPnz651t+oUaNo164db7zxBqtWrSIpKQmABg0aMHr0aLp165ZrY4ncro4ePcoDDzzAqVOngJQPl06nk4MHD3Lw4EGWLFnCli1bKFmyZIZ9/PTTT8adLMuXL880MZ+UlMRjjz1mzGQvUaIE9erV4/jx4+zfv59BgwaxYcMGvv766xs+t2sT5ZnVhj937hzx8fFUqFDhhmasu2YAZTYT6OLFi8D/zeAR+a/8KsF06dKlTMsqXbp0yXju+mK5atUqypQpk2778+fP07Fjx+te1E1ERERuPq7SMp6enlSqVCnDdn/99RdOp5NSpUoZn8tjY2ON5LiPjw9RUVGEhYUBpLuQ8ZYtW3jsscdYunQpTZo0SbXv0KFDAAQHBxvbypcvD8DZs2fT9HXgwAEAqlSpkuGEmejoaHr06MHq1atxc3Nj9uzZtG7dOt225cuXZ/369YwdOxabzUanTp348ssvAU28ERG5EUrMF7B69erx/fffY7PZOHv2LEWLFiUwMLCgwxK5Jdjtdrp06cKpU6eoUqUK06ZNo1mzZsTExDBv3jxGjRrFsWPHeO655zJdsNRVMxHg8OHDHDt2LMNajePGjWPZsmX4+/vz+eef07NnT0wmEwkJCYwaNYqPP/6YhQsX0qFDB3r37n1D5+dKkO/duzfVh/T/SkhIACA8PDzTdna7nfj4eO677z4WLVoEpNSOdHd3x9PTk8uXLwMpM3w+/PBDbDYbNpuN7t27G7fIHjt2DICQkJAbOje5deVXCSbX7K3t27en+nI7e/ZsnnjiiVQJdtcFq+rVq3PnnXemG7drfYTM7hgRERGRW4vr80S1atX4888/M2xntVpJSEhgwoQJ9O/fH4A1a9aQmJiIp6cnDz74oPEZBNIvDTlixAj+/fdf2rdvz8aNG6lbt66xz5Vod9V3B4wLBSdPnkzT1+bNm4GUO2vTs3//fnr16sXBgweNpPz777/PqFGj8PLyShWfw+EgLi6OypUrs2HDBmO76y7d3LgTWETkdqVvl4WE1WpVLXmRXLZ27VpjxuycOXO49957gZT32wsvvEBERAQTJkzg22+/5aOPPuKOO+5I04fD4WDlypWpti1fvpzhw4enaXvmzBk++OAD3N3dWb16tTEepNSN/PDDD/npp584dOgQc+fOveHEvOtDcGJiIv+PvfsOj6Jq+zj+2/RK7106RBCQLkiTjlKkCVJEAQtYEJDepAhSVUQFKQJSRAQEQZCmFAnSpHcIvQQICaRtdt8/8u48WdMh2RDy/VzXXs/szJkz9/BknN17z9wnJCQk3na2ba6urgm2syXmY85zMXXqVAUGBtq1u337tvr162e8r1ixosqWLav9+/fr1KlTkhRrtI0t1suXLyskJEQ+Pj6yWCx68OCBfH19k3K6eEo4qgRTYqO3YibmbT9y1a1bN97Eu+2pNr58AgCQcaTGaPD4PmusXr1adevW1fHjx9W4cWPt2LFDJUqU0N27d40R8zVq1DDa2wYK2T5/x2RLzP935L0kWSwWDRs2TEePHpWrq6sWLFig1157TcOHD0+wfG9i5T8BAMnn0MT8uXPndPPmzThvDint8OHDKlWqFPXOgAzs6NGjxnLMESc2zZs319SpUyVFjxpp1KhRrDa7du3SrVu35OHhoX79+mn8+PHxJuaPHTumGjVq6Nlnn7VLytuYTCZVqVJFx44ds5tI+lHZynwUK1YswZIdgwcP1meffaZBgwZp6NChyTpGhw4dZLVajaT+3LlzlSVLFnXp0sUYMV+gQAFFRkaqb9++kqQXX3xR5cuXt+snR44ckqLrXcZMxL/88stas2ZNsmJC+uaoEkwWiyVJccRsayt5BQBwrJif2dJifyA+jzqZa0LiS/bnypVLf/zxh2rVqqXz58+radOm2rVrl3bs2CGLxaICBQqocOHCRvtnnnlGnp6eunfvns6dO6eiRYtKin5K1nZN1KtXL85zWr16tcaNG6fq1aurYcOGkqJL6bi4uMjT09NuAIPZbNaDBw8SLTEIAEg+hyXm//zzT7366qtydnbWP//8owIFCqTasc6fP6969eqpZMmS+uWXX+IcBQvg6efj42Ms//XXX2rSpInd9hdeeEFhYWEJ9mErY1OvXj21b99e48ePN5L1OXPmtGvbuHFjNW7cOMH+rly5IkkpMkrc9uHYVvsyPrbyMiVLlkz2MWbOnGksnzlzRnPnzlX27Nn1xRdf2MXRvXt37dq1SyaTKc4a/H5+fnr//fe1a9cuhYSEyGw2y2q1xvmDCZ5ujijBJCnRL4+2/qX/JebPnz8fbymbCxcuJFhbFgCQfLbPQ0mZLDM5/QEpxdFPyuXLl0+bNm1SrVq1dPbsWbVq1crIZ7z88st2bZ2dnVWhQgXt3r1bmzZtUu/evSVJK1askNVqVd68eeOd+NXJyUnDhw+3W5dQjsbNzY1BjwCQChyWmPf09DRKJLRo0UJbtmxRtmzZUvw4t2/fVosWLXTnzh0dPHhQly9fJjEPZFAtW7ZU//79FRYWpm7duunrr79WmzZtkvUB25aYb9GihZ577jkVLFhQly5d0tq1a40akUl169Ytbdu2TZLiHJ2fXLYfFWJO6PTss88aJTdsAgICJEn9+/eP9QE8po8//lg9e/ZMdhxBQUHKkSOHXFxcNHr0aNWsWTPOdjNmzEh233j6OKIEk/S/xPvXX3+tVatWGettNVpjJuaTMwLsv9cXAODRlS5dWseOHVNwcPBj9+Xr65vgD7nAo0iLEnbFihXT2rVrVadOHe3evdtY36pVq1ht69atq927d2vDhg1GYn7ZsmWSor8LJebWrVtas2aNmjRpovz58ysoKEjjx4/XwYMH9fvvvxvtRo4cqeXLl+vFF1/U9OnTE3zqEQCQdA5LzFepUkXLli1T69atdfjwYTVq1EibNm1K0Tpld+7cUcOGDXX8+HGZTCbNmjVLzz//fIr1DyB9KVCggBYsWKAuXbro5s2batu2rUqXLq1evXqpe/fuif735+jRozpz5oyk6LI3ktSsWTN9++23Wr16dbIT82PHjpXZbJaXl5feeeedRzupGB4+fCjJfsT8xYsX401i2hL08Uko+RmfqKgoZcuWTSNHjlS7du1UqVIlRUVFpUo9TjwdHFGCSZKRqF+4cGGc22Mm5m0/cjVo0CDesjmRkZGSon9QAACkDJPJxITxeKIlVhovtTz//PNavHixWrduLavVKklxXivNmzfXhAkTtH79et25c0d37tzRjh07JEnt2rVL9Dg1a9bUmTNn9O2336pXr17y8vLSrFmzFBwcrBMnThg/dh0+fFjnzp1TiRIlSMoDQApK+YJpCWjevLmWLVsmV1dXHThwQDVq1IhzopJHceLECVWrVk3//vuvTCaTxo4dq27duqVI3wDSr/bt22vv3r1G7cQTJ06oX79+KlCggAYMGKD79+/Hu69ttPyzzz5r1HNs0aKFJGnjxo1GYjwpdu7cqa+++kqSNHz4cOXJk+eRzieme/fuSbJPzHt6ekqSlixZIqvVmqRXnTp1JNlPhpkQq9WqAwcOaNCgQSpYsKDCwsLUvXt3vfDCC/L09JSLi4tMJlOCL76EZ1yOKMEkSd9//70OHDigAwcOaN26dZKi55qwrYv59IgtiX/u3DmdPHkyzte5c+ckSQ8ePHikeAAAQPpjS8yfPn1apUuXjvdl++F+8ODBxrpevXrpvffeU69evVS6dGkNHjxYUtKf1GvZsqWKFy9uvO/QoYPdwAIpejLYvHnzKjw8XIsXL9aUKVNktVpVtGjROOvL/9crr7wiSfrjjz8kRT+paNvP9qSv9L8nDrt3756k2AEASePQyV8lqXXr1lq1apU6dOigU6dOqVq1apoyZcpj1RX8+uuvNXjwYOMRyHHjxhk3PQAoX768Nm7cqH///Vdz5szRvHnzFBISosmTJ2v58uVatWqVKlasGGs/W/kLWzJeih5RayvNtWnTpiQ9Inr79m299tprslgsqlWrVpwTxz6KO3fuSJLdqJXHGanu4eGR4HZbffxz586pUqVKduvz5s2rYsWK6cKFC4qKilKxYsXi7OPSpUuKiIhQs2bNHjlOpG+OKsFUokQJYzlLlizGMeOa1yAsLEw7duxQ7dq15evrq0uXLjEaDAAAGEn0iIiIBJ/0s7l+/bquX7+eYJuklsXbuHGjTp8+LRcXF1ksFu3evVtvv/225s2bZ7RxcnJSx44dNW3aNM2cOdP4/NSnT58kleFp2rSppk6dqs2bN8tiscjJyUmNGjXSmjVrtG3bNr399tsKDAxUQECAnJycEp1PCwCQPA4dMW/TpEkT/f333ypRooSCgoLUs2dP1alTR5s3b05WP+vWrVOVKlXUt29fBQcHy9vbW8uWLSMpDyBO5cuX1xdffKGAgAB9+OGHMplMCggIUMOGDWOVebl69ar++ecfSdLkyZPl4eEhDw8PZc2a1Ugs2kbUJ8RsNqt9+/a6dOmS8ubNq6VLl8rFJWV+E7127Zok+4mabIn5jz/+OMFRPTFf/v7+khRrQqeAgAAtXLhQ77//vkqWLKm6desa23LkyKF33nlHGzduVKFChTRr1iydOXNGVatWlSStXbtWZ86csXvt27fP+ILQvn37FPk3QPoTXwmm/45Qt41iDwgIiHcU+8mTJ+MtwbRnzx79/fffRgmaxAwbNkyS9P7775OUBwAAkv5X+s7Pzy/BJ1BtT57OmzfPWPfbb79p1apV+u2332S1Wu0S6kkpjTdp0iRJUs+ePTVkyBBJ0vz5842ncG1so9htn59y585t1JtPTO3ateXu7q47d+4Y331sI+a3b98uScb6ypUr25UCtZ0DZf4A4NE5fMS8TZkyZXTgwAENHjxYM2fO1F9//aVGjRqpdOnSatOmjerUqaNnn31WOXPmlLOzs8LCwnTz5k0dPHhQf/31l3766SddunTJqLdWt25dzZo1S6VKlUqrUwKQTmTNmlXTpk1TlSpV1LlzZwUGBurTTz/V7NmzjTZr1qwx/vtiNpvjHNmydu1aY2RJfN577z1t3bpVHh4eWrVqlfLnz59i52ErBRYzMW9z9erVx+7/5MmT6tq1q/E+b968unbtmgoVKqQzZ87EWYu7du3a2r17t3799ddYE7AtWLBA4eHhqlGjhqpVq/bY8SF9iq8EU0hIiJYsWaKOHTsmqZ+6detq+/bt8ZZgqlevnkJDQ40nSxIye/Zs48vnL7/8og0bNiS6T4sWLTRq1KgkxQoAANKnUqVKqWXLlkZZy8dRqFAh42lbs9kca1BMTD///LM2b94sT09PDR8+XLly5dKWLVu0a9cuffzxx6pevboqV64sKXrwUbly5YxyMxMnTky0ZKCNu7u7qlWrpj///FO///67qlatqjJlysjX11c3btzQ+fPntWfPHklSo0aN7Pa1DaJITnlPAIC9NBkxb+Pl5aUZM2Zo7969atGihaxWq44fP67x48ercePGyp8/v9zc3OTi4iJvb28988wzat26taZOnaqAgABZrVY9//zzWr58ubZs2UJSHoCdKlWqqHLlyvruu+/i3N6pUye98MILkqJrwMdkK2Njm3Ap5uvEiROSpFu3bmnXrl3xHn/ChAn67rvv5OTkpMWLFxujyVPK0aNHJSnOsjGPUmP+vxo2bKhixYqpfv36+v33343Epaura7wTZNrqVMYcESRFlwqZMmWKJGnAgAGPdsJ4KjiqBJOPj4/d/0rS/v379cwzzyh37tyaNWuWJMnf318ffPCBpOjyN8HBwdq3b5/+/fdfhYSE6O7du3bvAwICtG/fviQl/AEAQPr23nvvadWqVZoxY8Zj91W/fn2tWrVKq1atSjBxHhQUpL59+0qShgwZorx588rZ2VmLFy9W5syZFRERoU6dOhmJ8fXr1xvfCyTp4MGDsfq05Vr8/f1jvWyDfFatWiV/f3/t3btX48aN08aNG3Xr1i1jrp4CBQrI399fx48fl9VqJTEPACkgzUbMx1SxYkWtWbNGp0+f1pIlS7Ru3TodOnTIeCTKNmpViv4C7ufnp0aNGqlly5YpnugC8PQ4ceKEQkJCjNEjcbElB2OOWAkODtbWrVslRdeU/69SpUopf/78unLlilavXq1atWrFavPtt98aj5xOmzZNbdq0eaxz+S+r1apjx45Jiq7PnVr++OMPFSlSRJJ05syZRNvXrFlTzzzzjI4fP65169apefPmkqInvA0ICFD9+vXVunXrVIsXT77ESjAldRS6rfxUfKPNbD8exSwdFRoaqgsXLkiKfjT9yJEjatasmUJDQ9W+fXstW7ZMQ4YM0YQJE9S1a1fNmTNHy5cvV4cOHdS8eXP98ssvGj9+vIYOHapMmTIl67wBAAASExUVpU6dOunatWsqVaqUBg4caGwrUqSIvv32W3Xp0kXvvvuuPDw8tHPnTrVv314Wi0VFixbVuXPnNH36dOXJk0effPKJse+JEydUtmzZBI+9f//+BJ9qffvtt43lY8eOadiwYUYpQADAo3kiEvM2JUqU0IgRIzRixAhFRkbq0qVLunv3rsxms9zd3ZU1a1YVKlQoSZOYAECVKlW0detWI5nm6+trt/3q1avasWOH0dZm/fr1xg+D9evXj7PvevXqadGiRVq9erU+//xzu20zZ860G+Xy/vvvp9g52ezbt093795V1qxZlS9fvljbX3vtNb322muPfRxbUj6pTCaTPv74Y/Xp00cDBgxQgwYN9Ouvv2ry5MlydXXVl19++dgxIX1L7RJMNrbPCjE/M7zwwgvatm2bHjx4IBcXF3300UcKDAxU6dKl9e233+rWrVvGSHrbNbxkyRJJMiYsto0OIzEPAABS2ocffqjffvtNbm5uWrhwYawBCB06dFDlypVVrFgxbdy4UW3atNGDBw9UqVIlbd++XUOHDtUXX3yhQYMG6dq1a5o6daqcnJwUHBwsSZo7d678/PySHM+uXbv00UcfqWrVqurbt6/+/PNPzZ492yhNCAB4PE9UYj4mV1dXFS1aNK3DAJCO9e/fX1u3btWVK1dUu3ZtTZ48WS+88IIiIyPl7++vfv366f79+3JxcbFLntvK2OTNm1dlypSJs+/69etr0aJFOn36tI4fP260W7Rokfr06SNJ6t27t8aNG5cq52Z7pDS+p4ZcXV0TrH0fU0REhN2TSY/rrbfe0tSpU3X8+HG1bdtW27ZtkyR9/vnniY7UwdMvsRJMya0xn1wuLi7GkzLfffedmjRposqVK8vHx0eNGjXSvXv31LFjRz333HM6e/asfv31V7m7u+vVV1+VJGOy2f/+0AcAADKux/0sbbVa1a9fP2NiV9t8WHEpWrSoxo0bp5EjRyoqKkpVq1bVunXr5OPjo2nTpun27dv68ccfNWPGDB08eFBz5swx9vXz84v3+4PFYtHly5d1+vRpnTp1SqdOndKmTZskRZf+69Kli9H2ccoQAgD+54lNzAPA42rWrJkmTJigIUOG6NChQ2rYsKFMJpPdB2d3d3d9//33KleunCQpMjJSv/32m6S4y9jYxBxJv3r1apUpU0YWi8Wufvr8+fM1f/78ePs4efLkI08ktXr16lhxxPTDDz+keoIzPu7u7po7d67q1atn/IDQtm1bo443Mi5HlWBKjjZt2igiIkJdu3bV1q1blTdvXs2cOVOSNHbsWEVFRaldu3bKli2bJBkjzmLWrgcAABmb7Wlbs9n8SPv369dP06dPlxQ9av7dd9+Ns93FixfVq1cvbdy4UVL0/E4//vijvL29JUlOTk5atGiRcuTIoS+++ELbt29XuXLl1L59+1h9LVq0SIsXL9b169d1/fp13bp1S1FRUXEeN3fu3CpVqpSyZctmDGKKy/Xr1yWJKgcAkEQk5gE81QYNGqS6devqq6++0o4dO3Tt2jU5OzurUKFCatCggT744AOVLFnSaL99+3YFBQVJij/pLUmFCxc26jiuWrXKeFzU9mFUiq5hnZBHHVmzb98+HThwQJJStF57So2av3fvnubNm2fX3z///KP169eradOmKXIMpE+OKsGUHFevXlWnTp20fft2eXt7a+XKlcqWLZt27NihBQsWyGQyGfNFSDL++0ApGwAAINkn420J+uQaM2aMwsLCFBERoalTp8baHhwcrAkTJmjatGkKCwuTs7Ozxo0bp4EDB8ZKgptMJs2YMUPlypXT+++/r9DQUC1atEiS/ef9LFmyaMOGDXb7Zs+eXX5+fipXrpz8/PyMV/bs2SVFj5z/b2L+n3/+Ue/evSVJR44ckRT95DEAIHEk5gE89apXr67q1asnqe1LL72U5AT12bNn7d7nz58/RUvCxGf8+PGSoidaLVGihN022/EfJcEZFhaW4PbAwMAEtz948EDff/+9xo4dq1u3bsnV1VXvvPOO1q5dq3PnzqlZs2YqV66cunTpooYNG6pcuXI8BpvBPCklmB4+fKjAwEAdO3ZM7du31/379+Xh4aGVK1eqevXqunXrljp37iyr1aru3bsbT9RI/7sObOVwAABAxhaz3vqjJuZ9fX01a9YsWSyWOEebX716Vdu3b1dYWJieffZZzZkzJ8GJWqXo8pI1atRQt27d9NJLL2nixIl2fVeoUEG+vr6qXLmy+vfvrwoVKsQ5cCIxFSpUUEBAgG7fvi1J8vT0jHOEPgAgNhLzAJCObNiwQStXrpSkOB9xjYyMlCTly5cvyTWwAwICFBoaakxqGdOZM2c0depUOTs7a8uWLZJkNwnV+fPntWXLFq1fv14bNmzQgwcPJEUnXr/77js999xzmjRpkqZPn67Jkyfr8OHDGjhwoCTJ29tbpUqVUpUqVTRr1iweec0A0qoEk+1L8vnz59WwYUP99ddf6t+/v8aMGaOhQ4dq0qRJWrVqlWrVqqWQkBC1atVKAQEBKlCggKZMmWLX1+XLlyXJGDkGAAAytpiDVxIb6JKY+AYolCpVShs3btT8+fPVq1cvubq6Jqk/Pz8/7d27V3v37tXEiRPttvn6+ip79uzaunWrnJycjAnvk8vFxUUfffSRDh8+rIoVK6pt27bMFwgASURiHkCGYrVadeLECaNO9OPw9fVV6dKlUzWh/N94Dx8+rLZt2+rYsWN65pln5O/vb9felhh/55131KhRoyTFa0twxpWYf+aZZ7RixQrdunXLWGervR8VFaU+ffoYNfml6C8NQ4cO1euvv24cx93dXZ988on69u2ruXPnau7cuTpw4IAePHig/fv3a9y4cSTln0L//ds9fvy4UYKpaNGidn+7tsT5mTNnYv1NSwlfa/8dNX/u3DmtWLHCKDlTsmRJ4+mWq1ev6urVq8qVK5eKFy8uJycnDRw4UL1791bmzJkVGBioV155Rbt27ZKnp6dR1sbm2rVrOnfunKToJ2QAAABKlSrlkKdmvb299d577yV7v/g+Z2fOnFl79+5V586dtXHjRlWqVEkrVqxIdCR+XGKW/QMAJB2JeQAZyokTJ1S2bNkU6+/YsWMqU6ZMivX3XwnF+8ILL8S73/DhwzV8+PBY6+OKd9u2bfH24+zsrIYNG+r27dsqW7asatasqVatWhnbli5dqnLlyum5557TW2+9pebNm8c70sfLy0t9+vRRnz59dPz4ca1bt05nz55VkyZN4j0+0q+E/nbbtWsX5/r4/m4T8t+RaVmzZtXEiRMVEhIiSTp9+rQKFCig+vXrq3bt2nrxxRft5pWQor+Y7tmzR6+99prOnz8vd3d3rVq1SlWqVFFoaKhu3rypkydPasSIEYqKilLp0qXtEvYAAADpUY4cOfTbb79p1KhRGjt2rFq0aKEbN24kubQgAODxkJgHkKHYRu/OnTtXfn5+j9zP0aNH1aNHjxQZeZ+QJyHexYsXx7vN19dXZ86ckYtL8m4nZcqUSdUfNJD2Yv7t3r9/Xx9++KEkafTo0bF+jGnSpInu3r2rnDlzysvLy25beHi4rl+/rsKFC8vDw8NYH18JpqxZs6pbt27asWOHOnTooGbNmiX4t3bjxg2NGDFCc+bMkcViUebMmfXLL7+oXr16kqJHgE2fPt1o7+rqqkmTJiX73wMAAOBJ5OzsrE8//VR169bVpUuXSMoDgAORmAeQIfn5+cU7AeWT6EmON7lJeWQsfn5+unr1qt577z35+/tryJAhsf5mzGazJOmLL76IVWPe399f1apV0/Lly+2ugYRKME2ePDnJXypz5MihkiVLymKxqFSpUlq5cqXdSP/Ro0dr5syZioqKUv369TV69GjVrFkzyecPAACQHtjKVQIAHIdsCgAASFWtWrUySiDFJa7kemISKsGUnJFezs7O+vjjj1WgQAE1b95cPj4+dtszZcqkDRs2qFy5csqZM2ey4wQAAAAAIC4k5gHgKRIcHKydO3eqUaNGPIaKdCMyMjKtQ1CHDh3i3Va/fn0HRgIAAAAAyAjI2gDAU+LOnTuqW7eumjZtqmPHjqV1OAAAACnq7NmzaR0CAABAiiExDwD/cePGDQ0ZMkR3795N61CS7M6dO2rYsKH279+v119/3a5GNvCks1qtaR0CAKRbQ4cOVffu3bVo0SLdv38/rcNJNXv37lXJkiX15ptvJjtBHxkZqZCQED18+DCVogMAAEg+EvOAA+3atUstWrRQ5syZ5eTkJA8PDzVo0EBLly5N69AQw7Rp0zRhwgT9888/aR1Kkvw3KT9//nzK2CDdmDNnjrJly6Y//vgjrUMBgHRp586dWrBggcaOHSt3d/cU7Ts0NFR3795VeHi4oqKiEm3/22+/6bffftMff/yhv/76S3///Xe8r+Q83We1WvXBBx/IYrFo7ty5WrlyZbLOY8aMGfL19VWtWrWStR8AAEBqosY8MqygoCBNnz5dP//8s06fPi1nZ2cVKVJEL7/8sgYOHKisWbMmuP/Dhw+VI0cOhYaGatCgQZowYUKC7ZctW6bOnTsrKipKnp6eKl68uC5duqQtW7Zoy5Yt2rlzp7788suUPEU8ovXr18vFxUXVqlVL61ASZbFY1LRpU7ukvLOzc1qHBSTJDz/8oJ49eypLliwqWLBgWocDAOnSyZMnJUkfffRRrMT8yJEjNWfOHHl6esrV1VXOzs4KCQmR1WqVyWSym/D6hx9+UKVKlez2X7x4sXr27JmkOP766y917dpVgYGBSWrfvn17LVu2LEltZ8yYod27d0uS3N3dZTKZFB4enuQfInx9fSVJ2bJlS1J7AAAARyAxjwzp5MmTaty4sS5evChJMplMslqtOnr0qI4ePaqff/5ZO3bsUK5cueLtY9OmTQoNDZUkrV69OsHE/Pnz59WzZ09FRUVp6NChGjZsmDw8PBQcHKxRo0Zp6tSp+uqrr9S6dWsmGXwCFChQQFWqVFGmTJnSOpREmc1mPXjwQL169dLXX39NUh7pyo0bN1SyZEn99NNPKlWqVFqHAwDpzpUrV3T9+nU5OTnp1VdfjbX9wYMHunr1aqL9vPjii7GS8v/l7OwsZ2dnmUwmY53FYjEm8C5UqJBeeOEFbd26VcHBwfLz81OOHDli9bNv3z6FhISoePHiicYlSQcOHNAnn3wiSapQoYKOHj2qAQMGaObMmRo/frw6duxoF1NcXFyiv/ZmyZIlSccEnlZHjx5N0/0BAPZIzCPDiYyMVMuWLXXx4kUVK1ZM33zzjWrVqqWQkBAtXLhQn3zyiU6fPq0PPvhAS5Ysibef1atXG8vHjx/X6dOnVaJEiTjbDh06VMHBwXrzzTc1duxYY72vr6+mTJmi3bt3a/fu3Vq4cCGJ+SfAunXr0jqEJHNzc9ORI0fSOgzgkQwYMEADBgxI6zAAIN3466+/1Lx5c7m7u8vd3d2Yo8NkMqlatWqyWCwym80KCwtTxYoVtXTpUn3wwQdGezc3N23cuFERERH6/fff9f3338vJyUnTpk2L83hdunRRp06d5OXlFef2tWvX6uWXX5aLi4vy58+v1atXq1GjRtq0aZMGDBigbt26xdqnQIECCgkJifdzc0z3799Xx44dFRERoWeffVY7d+7UuXPn1Lt3b+3atUudOnXSjBkz9OWXX6pKlSqSpPHjx2vEiBFq3ry58XndNnAh5hMCQEZie2qkR48eKdofAODxkJhHhvP7778bj/wuWLBAL7zwgiTJw8NDH330kW7duqUJEyZo+fLlmj59unLnzh2rj6ioKK1du9Zu3erVq9W/f/9YbYOCgrR9+3a5urrq008/jTOmChUqaPfu3bp27drjnh4AAACeUhaLRaGhoUZCPiQkRFJ0kiwsLMwYwR4eHq6IiAhly5YtVvkWNzc3Xbt2TYsWLZIkvfPOO/GOlk+sVMzNmzclSYULFzaS33ny5JEk3bp1K1b70NBQYwR/YhPVm81mtWvXTqdOnVKmTJm0YsUKeXl56dlnn9WOHTv03XffadCgQdqzZ4+qVaumnj17auLEiXJ1dVVUVJS8vb0T7B/ISEqXLq1jx44pODj4sfvy9fVV6dKlUyAqAACJeWQ4MR+/q1ChQqztzZs319SpUyVJhw4dUqNGjWK12bVrl27duiUPDw/169dP48ePjzcxnzlzZl25ckXBwcHxjiy4fPmyJClfvnyPckoAAADIAOrUqWOUjpGkZ555RhcuXNDatWuNwSaJefDggSZOnKjw8HAVL15cn332WaL7hIWFycPDI9Z6W5I9Zjmy/PnzS1KcA07Onj1r1Lf38/OL93hms1kdO3bUxo0b5ebmpl9++cXuGCaTSb1791azZs3UrVs3bd26Vd99951atGhhxOnm5pboeQEZhclkUpkyZdI6DADAfzildQCAo8V8hPWvv/6Ktf2FF15QWFiYwsLC4kzKS/8rY1OvXj21b99e0v+S9fGJLyl//PhxbdiwQZLUunXrpJ0EAAAAMrS9e/fqwoULKliwoGrWrJmkfcLCwjR69GhduHBBUnRi/969ewnus2PHDhUtWlR///13rG3Hjh2TJLvRs7bJvG0DT2I6fPiwJKlYsWLxjmgPDg5Wy5Yt9fPPP8vJyUnz58+Pt9RjwYIF9ccff+iTTz7RBx98oJdfftlIzDPvDgAAeNKRmEeG07JlS+MDe7du3fTzzz8bjwMnlS0x36JFCz333HMqWLCgLBZLrPI2CYmKitKqVav00ksvKTIyUq+++qpefvnlZMUBAACAjGnevHmSpE6dOunu3buqXLmyKleurNOnT8fZ/u7du2revLkxN43JZNKmTZtUqlQpTZgwwW4kfkwDBgzQtWvX1KRJEx08eNBumy3RbqvvLkUn+yUZyf+YbINiqlWrFuexDh06pBo1aui3334zkvKff/65ChUqpFKlSunZZ581XmXKlFHhwoXVoEEDffbZZ5o+fbpxXjH/FwAA4ElFYh4ZToECBbRgwQK5ubnp5s2batu2rcqWLatp06bp7t27ie5/9OhRnTlzRlJ02RtJatasmST7CWET0q5dO+XIkUOtW7fW1atX1bt3b/3444+PeEYAAADISB4+fGh8duzevbvc3Ny0b98+7du3L86nNM+cOaPq1atry5YtcnJyUrdu3TRz5kw1bNhQDx8+1JAhQ1SpUiUdOHAg1r6rV69WmTJlFBQUpMaNGxuJ/7t37xoj5mvUqGG0t03qeurUqVh92RLz1atXj7XNYrFo2LBhOnr0qFxdXbVo0SJ16dJFd+7c0aVLl3Tq1CkdPXrUeJ04cUIBAQFJ+vwOAADwJCIxjwypffv22rt3rxo2bChJOnHihPr166cCBQpowIABun//frz72pLvzz77rAoXLiwpeuS8JG3cuFEPHz5M9Pjh4eEKCwsz3p88eVLnz59/5PMBAABAxvH1118rKChI9erVU+nSpe0mac2UKZOxbLVaNWfOHFWuXFmnTp2Sl5eXhgwZotatW6tIkSLauHGjFi9erOzZs+vIkSOqVq2apk2bZnesXLly6Y8//tAzzzyjmzdvqmnTprp586a2bt0qi8WiAgUKGJ+JpegR856enrp3757OnTtnrL9x44Yx11O9evVinZOTk5NWr16tMWPGaN26dXrttdckRZfSuXbtmu7du6fQ0FDjFRwcrOvXr+u3335LmX9UAAAAB3P45K+XLl3SvHnzZDKZNHz4cEcfHjCUL19eGzdu1L///qs5c+Zo3rx5CgkJ0eTJk7V8+XKtWrVKFStWjLXfqlWrJP0vGS9JDRo0kKenp0JDQ7Vp0ya1bNkywWOvWbNGYWFhWrt2rYYMGaJt27apXr162r17t90XG6SemJMAp8X+jj6eo+MFbPjbBYCU5e/vr1GjRkmSevfurZCQELuyjCEhIbpz547u3bun999/X1u3bpUUPUHrkiVLdP36dUVERBjtO3XqpDp16qhjx47asWOHfvrpJ/Xq1cuuBny+fPm0adMm1apVS2fPnlWrVq2UO3duSYpVitHZ2VkVKlTQ7t27tWnTJvXu3VuStGLFClmtVuXNmzfeiV+dnJxifUcsUKBAvP8Wbm5uTPIKAADSLYcn5q9fv65Ro0bJ1dX1kRPzlSpVSlI7V1dX5ciRQ/Xr19f7778vV1fXRzoenm7ly5fXF198odGjR2vMmDGaMWOGAgIC1LBhQ+3fv1+FChUy2l69elX//POPJGny5Ml2I4psX3BWr16daGJekjw8PNS2bVvVqlVLVapU0eXLlzVw4EAtW7Yshc8QMdke7+7Ro0eK9pda0lu8gA1/uwCQOjp16qQHDx5Ikjp27Bhruy1h/umnn6ps2bLaunWr3n77bU2ZMkVeXl5av359rH3y58+vzZs3a8SIERo0aFCcE7MWK1ZMa9euVZ06dbR7925jfatWrWK1rVu3rnbv3q0NGzYYiXnbZ9ykfE6+deuW1qxZoyZNmih//vwKCgrS+PHjdfDgQf3+++9Gu5EjR2r58uV68cUXNX36dGXOnDnRvgEAAJ4UDk/Me3p6SpLdyIawsDCFh4fL19dXTk721XUiIiJ079495cyZ05jA5+DBgzKZTIlO2Glrs2HDBkVFRWngwIEpfDZ4mmTNmlXTpk1TlSpV1LlzZwUGBurTTz/V7NmzjTZr1qwx/u7MZrPMZnOsftauXSuLxRLrbzk+efLk0ZtvvqnRo0dr06ZNKXMyiFfp0qV17NgxBQcHP3Zfvr6+Kl26dApEFb/0Fi9gw98uAKSOHj16aOrUqSpRooRy5swpDw8Pubu7a9GiRZKik/UPHz5UyZIlNWzYMHXr1s1uctb4uLm56bPPPkuwzfPPP6/FixerdevWxmfiMmXKxGrXvHlzTZgwQevXr9edO3d0584d7dixQ1L0XEuJqVmzps6cOaNvv/1WvXr1kpeXl2bNmqXg4GCdOHHCuCccPnxY586dU4kSJUjKAwCAdMfhiXkPDw9Jshu9vm7dOrVv3z7efUwmkwICApQvXz679Y0bNzb6+y+z2ayDBw/qypUrslqt2rx5M4l5SJKqVKkiq9WqXr16qVevXrG2d+rUSV9//bV27typnTt32m2zlbFp3bq1Vq5cabft5MmTKl26tG7duqVdu3apVq1axrbAwEAFBwerSJEiccZUqlQpSUqwtj1ShslkivML5JMqvcUL2PC3CwCpY/DgwRoyZEis9bbE/MKFC+Xi8r+veTNnztSmTZvk7u4uFxcXhYaGymq1ymQyycvLyxhsEh4ergYNGmjx4sUJHr9ly5YqXry4MQlshw4dtHXrVrs69zVq1FDevHl17do1LV68WMeOHZPValXRokXjrC//X6+88oqmTp2qP/74Q7169ZKrq6vq1aunNWvWaNu2bXaJeSl6AlwAAID0xuGJeduHxP/WAkxs9Htcvv/++1jJ+piOHj2qcuXKyWQy6fjx48nuH0+nEydOKCQkxPggHxfbiJuYf6fBwcFGjc4GDRrE2qdUqVLKnz+/rly5otWrVxuJ+dWrV6tVq1YqWLCgzp07Z/dFyebixYuSpLx58z76iQEAAOCpZ3uKOKlCQkJ09erVJLW1lchJyMaNG3X69Gm5uLjIYrFo9+7devvttzVv3jyjjZOTkzp27Khp06Zp5syZCggIkCT16dMnSfE3bdpUU6dO1ebNm40nURs1amQk5t9++20FBgYqICBATk5Oaty4cZLODwAA4EmStFobKciWlIw5Yv6ZZ55Rv379NGLECH366ad2r8eRNWtWY/nq1auKjIx8rP7wdLA9yvvLL7/EWWLh6tWrxqO2MR/7Xb9+vVFHvn79+nH2bRsBtHr1amNdnTp15OXlpUuXLhkTdcUUHh6ub775RpLUsGHDRzgjAAAA4H+sVqtOnjwpSfruu+907949hYWFKSoqSuvWrTPaWSwWRUVFKSwsTEFBQZo7d26ifU+aNEmS1LNnT2Pk/vz58/XVV1/ZtbONYj958qRCQ0OVO3duo958YmrXri13d3fduXPHmN/J9jl7+/btkmSsr1y5st33Ptvn9ZgT3AIAADyJHJ6Yt42QiDkSuVKlSpo8ebJGjRqloUOH2r2S6/Lly1q6dKmk6A+aUvSIjapVq+rhw4cpcAZI7/r37y9JunLlimrXrq0//vhDoaGhun//vv744w81adJE9+/fl4uLi95//31jP1sZm7x588ZbnsGWsD99+rTxlEaWLFnUr18/SdK4ceP0zjvv6MyZM7JYLDpz5oxat26tixcvysvLS4MHD06t0wYAAMBT6saNG8Zyx44dlTt3bmOASbZs2ZQ5c2a5u7vLycnJbsS6yWSSk5OT3N3dlSlTJmXLli3B4/z888/avHmzPD09NXz4cI0aNUo1a9aUJH388cdGslySypcvr3LlyhnvJ06cKC8vrySdj7u7u6pVqyZJxmSvZcqUka+vr27cuKHz589rz549kqRGjRrZ7RsaGipJfPcDAABPPIcn5m2cnZ0lRU/8+l+vvPKKbt++new+v/rqK/n5+alnz566evWqXF1dNWXKFF2/fl27du1iQiBIkpo1a6YJEybIZDLp0KFDatiwoby9vZU5c2Y1bNhQhw8flru7u+bPn298mYiMjNRvv/0mKe4yNjYxR9LHHDU/cuRIdejQQZL0zTffqESJEnJ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",
      "text/plain": [
       "<Figure size 1536x1024 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot\n",
    "# use a font that supports chinese characters\n",
    "plt.rcParams[\"font.family\"] = \"SimHei\"\n",
    "fig, axes = plt.subplots(2, 1, figsize=(6, 4), dpi=256)\n",
    "\n",
    "ax = axes[0]\n",
    "ax = scatterplot_with_text(\n",
    "    data=df,\n",
    "    x=\"adv\",\n",
    "    y=\"dist\",\n",
    "    text=\"move\",\n",
    "    marker=\"s\",\n",
    "    edgecolor=\"black\",\n",
    "    facecolor=\"none\",\n",
    "    s=25,\n",
    "    # hue=\"hkd\",\n",
    "    ax=ax,\n",
    "    # palette=\"viridis\",\n",
    ")\n",
    "# ax.get_legend().set_loc((1.01, 0))\n",
    "ax.grid(True)\n",
    "# ax.set_title(\"版中\")\n",
    "ax.spines[\"top\"].set_visible(False)\n",
    "ax.spines[\"right\"].set_visible(False)\n",
    "ax.set_xlabel(\"优势帧\")\n",
    "ax.set_ylabel(\"距离（版中）\")\n",
    "\n",
    "ax = axes[1]\n",
    "ax = scatterplot_with_text(\n",
    "    data=df,\n",
    "    x=\"adv\",\n",
    "    y=\"dist_edge\",\n",
    "    text=\"move\",\n",
    "    marker=\"s\",\n",
    "    edgecolor=\"black\",\n",
    "    facecolor=\"none\",\n",
    "    s=25,\n",
    "    # hue=\"hkd\",\n",
    "    ax=ax,\n",
    "    # palette=\"viridis\",\n",
    ")\n",
    "# ax.get_legend().set_loc((1.01, 0))\n",
    "ax.grid(True)\n",
    "# ax.set_title(\"版边\")\n",
    "ax.spines[\"top\"].set_visible(False)\n",
    "ax.spines[\"right\"].set_visible(False)\n",
    "ax.set_xlabel(\"优势帧\")\n",
    "ax.set_ylabel(\"距离（版边）\")\n",
    "\n",
    "from adjustText import adjust_text\n",
    "for ax in axes:\n",
    "    adjust_text(ax.texts, arrowprops=dict(arrowstyle='-', color='k', lw=0.5), ax=ax)\n",
    "\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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